Surviving and thriving in the 4th Industrial Revolution means a change in culture, adoption of new technologies and an ecosystem wide collaboration. We take a look at the market and the success and improvements surrounding the 3DEXPERIENCE Platform from Dassault Systemes.
Attaining IoT Value: How To Move from Connecting Things to Capturing InsightsSustainable Brands
Cisco estimates that the Internet of Everything (IoE) — the networked connection of people, process, data, and things — will generate $19 trillion in Value at Stake for the private and public sectors combined between 2013 and 2022. More than 42 percent of this value — $8 trillion — will come from one of IoE’s chief enablers, the Internet of Things (IoT). Defined by Cisco as “the intelligent connectivity of physical devices, driving massive gains in efficiency, business growth, and quality of life,” IoT often represents the quickest path to IoE value for private and public sector organizations.
This paper combines original and secondary research, as well as economic analysis, to provide a roadmap for maximizing value from IoT investments. It also explains why, in the worlds of IoT and IoE, the combination of edge computing/analytics and data center/cloud is essential to driving actionable insights that produce improved business outcomes.
The document summarizes the findings of a survey of 1,527 organizations in Melbourne and Victoria on their use of information and communication technology (ICT). Some key findings include: 71% use smartphones, 26% use IP telephony, 60% use Windows 7 as their operating system, 84% use laptops and 51% use tablets, 44% engage in teleworking, and 98% are connected to the internet mainly through broadband. The majority take steps to secure their networks and back up their data using methods like external hard drives, cloud storage, and tape backups.
This document discusses a survey of 354 top executives about how they locate business information. It finds that a generational shift is occurring as executives from "Generation PC" who came of age professionally during the rise of personal computers assume leadership positions. Generation PC executives access information more frequently, see greater value in emerging Internet technologies, and are willing to retrieve information in different ways, such as via video or mobile devices. The Internet is the top information resource for executives, who prefer to search for information themselves rather than delegating research. Search engines are the primary starting point, and executives are willing to click around online and follow links. Video and online networks are emerging tools for executives, though text remains preferred. IT executives are most likely to use
Law, Ethics and Tech Aspects for an Irrevocable BlockChain Based Curriculum V...eraser Juan José Calderón
Law, Ethics and Tech Aspects for an Irrevocable
BlockChain Based Curriculum Vitae Created by Big
Data Analytics Fed by Internet of Things, Sensors and
Approved Data Sources. Vasilios Kanavas, Athanasios Zisopoulos & Konstantinos Spinthiropoulos
The document discusses emerging challenges for digital businesses related to the Internet of Everything (IoE). It identifies 20 common challenges across markets/customers, business, and technology. The challenges include enabling IoE monetization, business model innovation, customer trust, workforce skills gaps, legacy systems, data ownership, standardization and more. The document aims to help leaders navigate the IoE landscape by providing insights into the most common challenges and how TM Forum can help organizations address them.
Monetizing the Internet of Things: Extracting Value from the Connectivity Opp...Capgemini
Cisco has estimated that the Internet of Things (IoT) has the potential to generate about $19 trillion of value over the coming years. The staggering potential size-of-the-prize has certainly caught the attention of the world’s business community. In a recent survey of senior business leaders around the globe, 96% said their companies would be using IoT in some way within the next 3 years. However, there is a catch – most organizations are yet to derive significant commercial value from IoT. Our research shows that 70% of organizations do not generate service revenues from their IoT solutions. We have looked at why organizations are falling short in monetizing the IoT, and have tried to capture some initial observations on monetization models in what is still a very fast-developing marketplace.
Surviving and thriving in the 4th Industrial Revolution means a change in culture, adoption of new technologies and an ecosystem wide collaboration. We take a look at the market and the success and improvements surrounding the 3DEXPERIENCE Platform from Dassault Systemes.
Attaining IoT Value: How To Move from Connecting Things to Capturing InsightsSustainable Brands
Cisco estimates that the Internet of Everything (IoE) — the networked connection of people, process, data, and things — will generate $19 trillion in Value at Stake for the private and public sectors combined between 2013 and 2022. More than 42 percent of this value — $8 trillion — will come from one of IoE’s chief enablers, the Internet of Things (IoT). Defined by Cisco as “the intelligent connectivity of physical devices, driving massive gains in efficiency, business growth, and quality of life,” IoT often represents the quickest path to IoE value for private and public sector organizations.
This paper combines original and secondary research, as well as economic analysis, to provide a roadmap for maximizing value from IoT investments. It also explains why, in the worlds of IoT and IoE, the combination of edge computing/analytics and data center/cloud is essential to driving actionable insights that produce improved business outcomes.
The document summarizes the findings of a survey of 1,527 organizations in Melbourne and Victoria on their use of information and communication technology (ICT). Some key findings include: 71% use smartphones, 26% use IP telephony, 60% use Windows 7 as their operating system, 84% use laptops and 51% use tablets, 44% engage in teleworking, and 98% are connected to the internet mainly through broadband. The majority take steps to secure their networks and back up their data using methods like external hard drives, cloud storage, and tape backups.
This document discusses a survey of 354 top executives about how they locate business information. It finds that a generational shift is occurring as executives from "Generation PC" who came of age professionally during the rise of personal computers assume leadership positions. Generation PC executives access information more frequently, see greater value in emerging Internet technologies, and are willing to retrieve information in different ways, such as via video or mobile devices. The Internet is the top information resource for executives, who prefer to search for information themselves rather than delegating research. Search engines are the primary starting point, and executives are willing to click around online and follow links. Video and online networks are emerging tools for executives, though text remains preferred. IT executives are most likely to use
Law, Ethics and Tech Aspects for an Irrevocable BlockChain Based Curriculum V...eraser Juan José Calderón
Law, Ethics and Tech Aspects for an Irrevocable
BlockChain Based Curriculum Vitae Created by Big
Data Analytics Fed by Internet of Things, Sensors and
Approved Data Sources. Vasilios Kanavas, Athanasios Zisopoulos & Konstantinos Spinthiropoulos
The document discusses emerging challenges for digital businesses related to the Internet of Everything (IoE). It identifies 20 common challenges across markets/customers, business, and technology. The challenges include enabling IoE monetization, business model innovation, customer trust, workforce skills gaps, legacy systems, data ownership, standardization and more. The document aims to help leaders navigate the IoE landscape by providing insights into the most common challenges and how TM Forum can help organizations address them.
Monetizing the Internet of Things: Extracting Value from the Connectivity Opp...Capgemini
Cisco has estimated that the Internet of Things (IoT) has the potential to generate about $19 trillion of value over the coming years. The staggering potential size-of-the-prize has certainly caught the attention of the world’s business community. In a recent survey of senior business leaders around the globe, 96% said their companies would be using IoT in some way within the next 3 years. However, there is a catch – most organizations are yet to derive significant commercial value from IoT. Our research shows that 70% of organizations do not generate service revenues from their IoT solutions. We have looked at why organizations are falling short in monetizing the IoT, and have tried to capture some initial observations on monetization models in what is still a very fast-developing marketplace.
Why IT does not matter in Exponential OrganizationsSrinivas Koushik
The document discusses how traditional IT organizations need to change to support exponential organizations (ExOs). It notes that ExOs focus on delivering secure, seamless experiences through technology and data. Traditional IT will need to adopt approaches like smart creatives, lightweight integration, agile insights, and active ecosystem engagement to enable ExOs. ExOs are built for rapid change and focus on delivering massive transformational purposes through open platforms and engaged communities.
The document discusses the need for a new approach to managing IT in today's digital businesses. It argues that traditional IT models focused on stability and accuracy are no longer suitable and that IT must become more agile to enable business agility. Several existing frameworks for managing hybrid legacy and new systems are described but found lacking. A new approach is needed to help IT organizations adapt and deliver the fast, flexible capabilities required for digital business success.
Governance: a central component of successful digital transformationPaula Calvo Lopez
Companies need firm-level governance around digital initiatives to address new challenges from faster business cycles, new risks, and the need for more integration. Governance mechanisms implemented include shared digital units, firm-level committees, and new digital roles. Shared digital units develop skills and services, committees make decisions on investments and policies, and new roles drive strategy and adoption of shared capabilities. These mechanisms help coordination of initiatives and sharing of resources, with benefits including standards, consistency, and optimization, but also challenges in areas like structure and change management. An important objective of governance is building enterprise platforms to provide integrated views and enable advanced capabilities and services.
With the covid-19 outbreak, digital transformation in industries got boosted. Organizations started relying on digital platforms to achieve their objectives during these vulnerable times. Employees are now expected to learn digital ethics in order to maintain decorum on digital platforms. Digital ethics are organizational, social, and interpersonal norms.
Artificial intelligence (AI) refers to a constellation of technologies, including machine learning, perception, reasoning, and natural language processing. While the field has been pursuing principles and applications for over 65 years, recent advances, uses, and attendant public excitement have returned it to the spotlight. The impact of early AI 1 systems is already being felt, bringing with it challenges and opportunities, and laying the foundation on which future advances in AI will be integrated into social and economic domains. The potential wide-ranging impact make it necessary to look carefully at the ways in which these technologies are being applied now, whom they’re benefiting, and how they’re structuring our social, economic, and interpersonal lives.
Report 2 empathic things – intimate technology - from wearables to biohackin...Rick Bouter
In the second report we focused on the personalized internet of things. We are witnessing a computer boom in terms of kinds, shapes and sizes – around, on or inside the body. Therefore we explored the coming transition toward a more empathic and contextual form of computerization. The emergence of wearable computing and other forms of empathic ‘things’ seems a logical further step: even more intimate, more human-oriented, and ubiquitous. We explored this development and present seven manifestations that can define the impact on business, such as the ‘quantified employee’ and the ‘body as the new password’.
Source, Sogeti ViNT: http://vint.sogeti.com/internet-things-4-reports/
The Efma–Accenture Innovation in Insurance Awards were launched in 2016 to recognize and promote innovation in the industry. Encouraging insurers to explore new ways of growing their business, the awards celebrate the best new ideas that are transforming our industry – and serve to spark further innovation.
The awards continue to grow in their reach and importance, with 395 submissions received in 2019 from 287 carriers in 54 countries across the globe. Winners were announced on June 24 at the global awards ceremony in Amsterdam, and a second ceremony specifically recognizing US and Canadian innovation will now take place in Chicago on November 6.
Learn more: https://www.accenture.com/us-en/event-efma-accenture-insurance-innovation-awards
HorizonWatching: How IBM Develops Views of the Potential FuturesBill Chamberlin
This deck provides an overview of eight initiatives at IBM designed to help IBM understand emerging trends, technologies, and business issues that will face IBM and our customers in the future.
This study examined the impact of information and communication technologies (ICT) on the financial services sector. The researcher conducted primary and secondary research, including a questionnaire. The study found that ICT has significantly impacted the sector through technologies like mobile banking, mobile pay, and blockchain. However, cybersecurity issues and low internet accessibility were major challenges reported. Respondents were also less aware of automated wealth managers and data processing. Overall, the study concluded that ICT has greatly influenced financial services, but authorities must address security problems and increase awareness of certain technologies.
The document discusses how the Internet of Everything (IoE) will create $14.4 trillion in value for companies over the next decade. It identifies five main drivers of this value: improved asset utilization, employee productivity, supply chain efficiency, customer experience, and innovation. It provides examples of high-value IoE use cases including smart factories, which are expected to create $1.95 trillion in value through cost reductions, revenue growth, and better workforce collaboration enabled by machine-to-machine connectivity and data analytics. The document encourages business leaders to transform their organizations based on lessons from top IoE use cases in order to capture value from the IoE.
This document summarizes a presentation on innovation in entrepreneurship given by Bohitesh Misra. The presentation covers types of innovation, sources and barriers of innovation, and the importance of frugal innovation. It discusses how digital technology boosts frugal innovation through mobile phones and biometric authentication. Frugal innovation focuses on customer needs and offers more agile, customer-centric products at lower costs through simplification and minimum inputs.
How has covid 19 impacted mobile app development projectsMaryamMiahan
This pandemic outbreak has affected almost everything and of course mobile app development industry also, but it has raised the mobile app demand in market now. Visit: https://www.appsquadz.com
Mobile devices present new challenges for backing up data as more employees use their personal smartphones and tablets for work. IT needs to implement a smart mix of policies, cloud services, and mobile device management to address these challenges. Specifically, the policy should clearly define the company's requirements for accessing corporate data on personal devices and clarify IT's responsibilities for backing up corporate versus personal data. The cloud can help with backups, but full device backups are difficult due to limitations of mobile operating systems.
https://iot-eurasia.com/
"IOT will completely transform the way we do business, in a staggered manner such that most of the business transactions will become near real time or real time, enabled by IOT. IOT also helps us to get additional data points which is not possible in non-IOT setup. These additional data points generate additional value or enhances the existing value. Few examples to quote include real time patient data (vital signs, quality of life, etc.), real-time manifacturing, drug supply and also predict the demand and supply drug. The next level of competitive advantage can be derived when we add advanced analytics capabilities to unlock the insights from IOT and other traditional data points. Predictive analytics take decision making to the next level, where almost all decisions can be made better."
"In order to move business beyond main areas, industries will have to secure partnerships with good IoT platforms. For instance, transforming Telco into an ICT (Information and communication technologies) organization by offering Digital services such as IoT Application Enablement Platform (AEP) and M2M Connectivity Platforms. A telecommunication firm has a unique opportunity to drive mobile payments – by building on direct carrier billing through multiple payment options, data management and seamless fulfilment – to the next level. Also, faster adoption of cloud, big data and cyber technologies would ensure delivering impeccable network, platform and solution functionalities."
This document discusses how technology is changing the nature of jobs and the future of work. Key points:
1) Digital technologies are automating routine tasks and jobs that involve structured processes, while human workers will likely shift toward tasks requiring creativity, social skills and innovative thinking.
2) New online platforms are creating "networked work" where freelancers connect directly with clients, taking on more risks but also gaining more control over their work. However, this transition to more flexible work arrangements is not painless.
3) Demand is growing for STEM jobs across many industries as data analysis and computing become more widespread. While some jobs will be automated, technology also has the potential to create new types of jobs
Australian Enterprises for the Digital EconomyVishal Sharma
This document summarizes research conducted by the National Institute of Economic and Industry Research (NIEIR) on how digital technologies will impact seven key industry sectors in Australia by 2025. The research models two potential futures for enterprises in each sector: a "leader" that fully embraces digital transformation, and a "follower" that does not significantly change. It finds that large performance gaps will open up between leaders and followers, with leaders enjoying significant advantages in areas like revenue, market share, and productivity. By 2025, these gaps could be worth hundreds of billions of dollars in combined market capitalization across some sectors. The research underscores the importance of Australian enterprises urgently transforming their business models for the digital age.
Design to Disrupt - Blockchain: cryptoplatform for a frictionless economyRick Bouter
This document provides an overview of the cryptocurrency and blockchain technology known as Bitcoin and the potential implications of its underlying blockchain technology. It discusses Bitcoin and blockchain in three phases: 1) Crypto-economy 1.0 focuses on Bitcoin as a digital currency and financial transactions. 2) Crypto-economy 2.0 explores additional applications of blockchain technology such as smart contracts and connected devices. 3) Crypto-economy 3.0 envisions a future of decentralized autonomous organizations where digital objects and entities can make autonomous decisions. The document aims to outline how this new blockchain-based trust model could transform and disrupt many industries by enabling new forms of digital value and transactions.
Role of Information & Communication Technology in Developing the Banking Sect...ijtsrd
Today Information& Communication Technology is not only for computer literacy, it also deals with how computers work and how these computers can further be used not just for information processing but also for communications and problem solving tasks as well. The significance of ICT can be seen from the fact that it has penetrated almost every aspect of our daily lives from business to leisure and even society and social development. The 21st century will bring about an all-embracing convergence of computing, communications and informations. This explosion of technology is changing the banking industry from paper and branch banks to digitized and networked banking services. All over the world, banks are still struggling to find a technological solution to meet the challenges of a rapidly-changing environment. The present article presents the role of Computer Science as well as Information& Communication Technology in developing the banking industry in India. Smt Paramita Chatterjee"Role of Information & Communication Technology in Developing the Banking Sector of India" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-2 , February 2018, URL: http://www.ijtsrd.com/papers/ijtsrd10710.pdf http://www.ijtsrd.com/computer-science/data-processing/10710/role-of-information-and-communication-technology-in-developing-the-banking-sector-of-india/smt-paramita-chatterjee
How will social media and other new technologies impact our industry the next...Atle Skjekkeland
This document discusses how new technologies like social media will impact industries in the next 5-10 years. It outlines how consumer technologies have evolved more rapidly than enterprise technologies, and how this is changing customer and employee expectations. The rise of systems of engagement and user-generated content requires new approaches to content management, security, and integration with existing systems of record. The document proposes strategies like leveraging early adopters, prioritizing mobile and social capabilities, and creating policies and taxonomies to manage social content responsibly and achieve business goals.
Why IT does not matter in Exponential OrganizationsSrinivas Koushik
The document discusses how traditional IT organizations need to change to support exponential organizations (ExOs). It notes that ExOs focus on delivering secure, seamless experiences through technology and data. Traditional IT will need to adopt approaches like smart creatives, lightweight integration, agile insights, and active ecosystem engagement to enable ExOs. ExOs are built for rapid change and focus on delivering massive transformational purposes through open platforms and engaged communities.
The document discusses the need for a new approach to managing IT in today's digital businesses. It argues that traditional IT models focused on stability and accuracy are no longer suitable and that IT must become more agile to enable business agility. Several existing frameworks for managing hybrid legacy and new systems are described but found lacking. A new approach is needed to help IT organizations adapt and deliver the fast, flexible capabilities required for digital business success.
Governance: a central component of successful digital transformationPaula Calvo Lopez
Companies need firm-level governance around digital initiatives to address new challenges from faster business cycles, new risks, and the need for more integration. Governance mechanisms implemented include shared digital units, firm-level committees, and new digital roles. Shared digital units develop skills and services, committees make decisions on investments and policies, and new roles drive strategy and adoption of shared capabilities. These mechanisms help coordination of initiatives and sharing of resources, with benefits including standards, consistency, and optimization, but also challenges in areas like structure and change management. An important objective of governance is building enterprise platforms to provide integrated views and enable advanced capabilities and services.
With the covid-19 outbreak, digital transformation in industries got boosted. Organizations started relying on digital platforms to achieve their objectives during these vulnerable times. Employees are now expected to learn digital ethics in order to maintain decorum on digital platforms. Digital ethics are organizational, social, and interpersonal norms.
Artificial intelligence (AI) refers to a constellation of technologies, including machine learning, perception, reasoning, and natural language processing. While the field has been pursuing principles and applications for over 65 years, recent advances, uses, and attendant public excitement have returned it to the spotlight. The impact of early AI 1 systems is already being felt, bringing with it challenges and opportunities, and laying the foundation on which future advances in AI will be integrated into social and economic domains. The potential wide-ranging impact make it necessary to look carefully at the ways in which these technologies are being applied now, whom they’re benefiting, and how they’re structuring our social, economic, and interpersonal lives.
Report 2 empathic things – intimate technology - from wearables to biohackin...Rick Bouter
In the second report we focused on the personalized internet of things. We are witnessing a computer boom in terms of kinds, shapes and sizes – around, on or inside the body. Therefore we explored the coming transition toward a more empathic and contextual form of computerization. The emergence of wearable computing and other forms of empathic ‘things’ seems a logical further step: even more intimate, more human-oriented, and ubiquitous. We explored this development and present seven manifestations that can define the impact on business, such as the ‘quantified employee’ and the ‘body as the new password’.
Source, Sogeti ViNT: http://vint.sogeti.com/internet-things-4-reports/
The Efma–Accenture Innovation in Insurance Awards were launched in 2016 to recognize and promote innovation in the industry. Encouraging insurers to explore new ways of growing their business, the awards celebrate the best new ideas that are transforming our industry – and serve to spark further innovation.
The awards continue to grow in their reach and importance, with 395 submissions received in 2019 from 287 carriers in 54 countries across the globe. Winners were announced on June 24 at the global awards ceremony in Amsterdam, and a second ceremony specifically recognizing US and Canadian innovation will now take place in Chicago on November 6.
Learn more: https://www.accenture.com/us-en/event-efma-accenture-insurance-innovation-awards
HorizonWatching: How IBM Develops Views of the Potential FuturesBill Chamberlin
This deck provides an overview of eight initiatives at IBM designed to help IBM understand emerging trends, technologies, and business issues that will face IBM and our customers in the future.
This study examined the impact of information and communication technologies (ICT) on the financial services sector. The researcher conducted primary and secondary research, including a questionnaire. The study found that ICT has significantly impacted the sector through technologies like mobile banking, mobile pay, and blockchain. However, cybersecurity issues and low internet accessibility were major challenges reported. Respondents were also less aware of automated wealth managers and data processing. Overall, the study concluded that ICT has greatly influenced financial services, but authorities must address security problems and increase awareness of certain technologies.
The document discusses how the Internet of Everything (IoE) will create $14.4 trillion in value for companies over the next decade. It identifies five main drivers of this value: improved asset utilization, employee productivity, supply chain efficiency, customer experience, and innovation. It provides examples of high-value IoE use cases including smart factories, which are expected to create $1.95 trillion in value through cost reductions, revenue growth, and better workforce collaboration enabled by machine-to-machine connectivity and data analytics. The document encourages business leaders to transform their organizations based on lessons from top IoE use cases in order to capture value from the IoE.
This document summarizes a presentation on innovation in entrepreneurship given by Bohitesh Misra. The presentation covers types of innovation, sources and barriers of innovation, and the importance of frugal innovation. It discusses how digital technology boosts frugal innovation through mobile phones and biometric authentication. Frugal innovation focuses on customer needs and offers more agile, customer-centric products at lower costs through simplification and minimum inputs.
How has covid 19 impacted mobile app development projectsMaryamMiahan
This pandemic outbreak has affected almost everything and of course mobile app development industry also, but it has raised the mobile app demand in market now. Visit: https://www.appsquadz.com
Mobile devices present new challenges for backing up data as more employees use their personal smartphones and tablets for work. IT needs to implement a smart mix of policies, cloud services, and mobile device management to address these challenges. Specifically, the policy should clearly define the company's requirements for accessing corporate data on personal devices and clarify IT's responsibilities for backing up corporate versus personal data. The cloud can help with backups, but full device backups are difficult due to limitations of mobile operating systems.
https://iot-eurasia.com/
"IOT will completely transform the way we do business, in a staggered manner such that most of the business transactions will become near real time or real time, enabled by IOT. IOT also helps us to get additional data points which is not possible in non-IOT setup. These additional data points generate additional value or enhances the existing value. Few examples to quote include real time patient data (vital signs, quality of life, etc.), real-time manifacturing, drug supply and also predict the demand and supply drug. The next level of competitive advantage can be derived when we add advanced analytics capabilities to unlock the insights from IOT and other traditional data points. Predictive analytics take decision making to the next level, where almost all decisions can be made better."
"In order to move business beyond main areas, industries will have to secure partnerships with good IoT platforms. For instance, transforming Telco into an ICT (Information and communication technologies) organization by offering Digital services such as IoT Application Enablement Platform (AEP) and M2M Connectivity Platforms. A telecommunication firm has a unique opportunity to drive mobile payments – by building on direct carrier billing through multiple payment options, data management and seamless fulfilment – to the next level. Also, faster adoption of cloud, big data and cyber technologies would ensure delivering impeccable network, platform and solution functionalities."
This document discusses how technology is changing the nature of jobs and the future of work. Key points:
1) Digital technologies are automating routine tasks and jobs that involve structured processes, while human workers will likely shift toward tasks requiring creativity, social skills and innovative thinking.
2) New online platforms are creating "networked work" where freelancers connect directly with clients, taking on more risks but also gaining more control over their work. However, this transition to more flexible work arrangements is not painless.
3) Demand is growing for STEM jobs across many industries as data analysis and computing become more widespread. While some jobs will be automated, technology also has the potential to create new types of jobs
Australian Enterprises for the Digital EconomyVishal Sharma
This document summarizes research conducted by the National Institute of Economic and Industry Research (NIEIR) on how digital technologies will impact seven key industry sectors in Australia by 2025. The research models two potential futures for enterprises in each sector: a "leader" that fully embraces digital transformation, and a "follower" that does not significantly change. It finds that large performance gaps will open up between leaders and followers, with leaders enjoying significant advantages in areas like revenue, market share, and productivity. By 2025, these gaps could be worth hundreds of billions of dollars in combined market capitalization across some sectors. The research underscores the importance of Australian enterprises urgently transforming their business models for the digital age.
Design to Disrupt - Blockchain: cryptoplatform for a frictionless economyRick Bouter
This document provides an overview of the cryptocurrency and blockchain technology known as Bitcoin and the potential implications of its underlying blockchain technology. It discusses Bitcoin and blockchain in three phases: 1) Crypto-economy 1.0 focuses on Bitcoin as a digital currency and financial transactions. 2) Crypto-economy 2.0 explores additional applications of blockchain technology such as smart contracts and connected devices. 3) Crypto-economy 3.0 envisions a future of decentralized autonomous organizations where digital objects and entities can make autonomous decisions. The document aims to outline how this new blockchain-based trust model could transform and disrupt many industries by enabling new forms of digital value and transactions.
Role of Information & Communication Technology in Developing the Banking Sect...ijtsrd
Today Information& Communication Technology is not only for computer literacy, it also deals with how computers work and how these computers can further be used not just for information processing but also for communications and problem solving tasks as well. The significance of ICT can be seen from the fact that it has penetrated almost every aspect of our daily lives from business to leisure and even society and social development. The 21st century will bring about an all-embracing convergence of computing, communications and informations. This explosion of technology is changing the banking industry from paper and branch banks to digitized and networked banking services. All over the world, banks are still struggling to find a technological solution to meet the challenges of a rapidly-changing environment. The present article presents the role of Computer Science as well as Information& Communication Technology in developing the banking industry in India. Smt Paramita Chatterjee"Role of Information & Communication Technology in Developing the Banking Sector of India" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-2 , February 2018, URL: http://www.ijtsrd.com/papers/ijtsrd10710.pdf http://www.ijtsrd.com/computer-science/data-processing/10710/role-of-information-and-communication-technology-in-developing-the-banking-sector-of-india/smt-paramita-chatterjee
How will social media and other new technologies impact our industry the next...Atle Skjekkeland
This document discusses how new technologies like social media will impact industries in the next 5-10 years. It outlines how consumer technologies have evolved more rapidly than enterprise technologies, and how this is changing customer and employee expectations. The rise of systems of engagement and user-generated content requires new approaches to content management, security, and integration with existing systems of record. The document proposes strategies like leveraging early adopters, prioritizing mobile and social capabilities, and creating policies and taxonomies to manage social content responsibly and achieve business goals.
The top trends changing the landscape of Information ManagementVelrada
The role of information and data in the private sector, and how employees and users interact with that information, is changing rapidly.
With endless buzzwords and hot topics, and a ream of new technologies and upgrades, it can be difficult for organisations to know where to begin or how it translates into actionable insight.
This document discusses trends in innovation, including the sharing economy, big data, and social computing. It provides examples of how companies like Kodak and Instagram demonstrate how innovation is changing. The sharing economy is leveraging unused assets and network effects to create services. Big data is growing exponentially in terms of volume, variety, and velocity. Social computing uses enterprise 2.0 approaches to access micro-expertise within organizations. These trends are enabling new, data-driven business models and approaches to open innovation within large companies. Skills and processes are needed to design inclusive innovation processes and implement platforms that can monitor and evaluate these new approaches.
Computer Application in Business Group Presentation2023210000518
The document provides an overview of a group presentation on computer applications in business. It discusses how information systems have rapidly evolved since the 1950s and how current technologies are more powerful than those used to land on the moon. The document also includes case study questions and answers about challenges of transforming IT from a support role to strategic partner, implications for IT workers and education, and examples of how technology is embedded in companies.
Emerging Trends in AI and data science IN KRCTkrctseo
In this era of technology, Artificial Intelligence (AI) stand as the pillar of innovation, driving changes across all industries and even society as a whole. As we look into the future, it’s essential to notice the emerging trends in AI shaping the trajectory of our world. These trends are paving the way for new possibilities and advancements in all aspects of life.
Presentation about the state of AI, policy-relevant AI research and evidence gaps that can be addressed with new data, methods and modelling approaches.
Ethical Dimensions of Artificial Intelligence (AI) by Rinshad ChoorapparaRinshad Choorappara
This document discusses the ethical dimensions of artificial intelligence. It begins with definitions of AI and ethics. It then discusses how AI is revolutionizing industries like healthcare, finance, transportation, and more. However, it also notes challenges of AI like bias, lack of transparency, job displacement, privacy and security issues. It provides examples of authorities like the European Union and United Nations taking action to address these issues and ensure ethical governance of AI through frameworks like the EU Artificial Intelligence Act. The document emphasizes the importance of balancing AI innovation with ethical considerations to build trust and align AI with human values.
This 3-page document provides an executive summary of a report on how AI is transforming the customer experience. It discusses how AI will become ubiquitous in the next 5 years and profoundly shape interactions with companies through technologies like chatbots and augmented reality. It also outlines some of the key challenges AI poses for customer experience, such as new interaction models, information asymmetry, and the amplification of biases. The summary concludes by emphasizing the need for business leaders to establish principles to ensure AI is developed and applied in a customer-centric manner.
Article started one year ago, obtains far more relevancy these days. Its meaning stays the same however: "Without laws and regulations would be chaos affecting our freedom and human nature."
The new fundamentals-Seizing opportunities with AI in the cognitive economyLynn Reyes
We are in a new era of exponential learning and the world is transitioning to a cognitive economy. All—organizations, industries, governments, individuals—are learning, interacting in dynamic ecosystems and augmenting intelligence at increasing scales. Disruptive forces are reshaping societies and economies; and the impact of technology is especially profound. Data, emerging technologies and cyber-turbulence will continue to fuel disruption into the future. Leaders will also need to become agile visionary doers. Government will play a critical role in establishing the foundation of a knowledge-based, learning society. New fundamentals are needed.
The document discusses various aspects of industrial revolutions and Industry 4.0:
- It describes the four industrial revolutions - the first involved steam power, the second involved electricity, the third involved computers and ICT, and the fourth involves advanced automation through cyber-physical systems.
- It outlines some challenges of Industry 4.0 including unclear economic incentives, adapting workforces, data security concerns, and understanding customer needs.
- It then discusses collaborative innovation networks (COINs), how they operate through self-organized teams, different member roles, advantages like better processes and relationships, and barriers like access issues and cultural resistance.
ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING Goodbuzz Inc.
Driving Tangible Value for Business. Briefing Paper. Interest in AI/ML is soaring, but confusion and hype can mask the real benefits of these technologies. Organizations need to identify use cases that will produce value for them, especially in the areas of enhancing processes, detecting anomalies and enabling predictive analytics.
What should organizations be concerned about when using Machine Learning for Predictive Modeling techniques? Divergence Academy and Divergence.AI are leading efforts to bring Algorithmic Accountability awareness to masses.
In this video from the Global Tech Jam 2018, Jerry Power from the USC Marshall School of Business presents: Global Tech Jam: I3 Intelligent IoT Integrator.
Watch the video: http://insidesmartcities.com/global-tech-jam-video-i3-intelligent-iot-integrator/
Learn more: http://i3.usc.edu
https://globaltechjam.com/2018-global-tech-jam-presentations/
and
http://insideSmartCities.com
In this video from the Global Tech Jam 2018, Jerry Power from the USC Marshall School of Business presents: Global Tech Jam: I3 Intelligent IoT Integrator.
Watch the video: http://insidesmartcities.com/global-tech-jam-video-i3-intelligent-iot-integrator/
Learn more: https://globaltechjam.com/2018-global-tech-jam-presentations/
and
http://insideSmartCities.com
Artificial Intelligence Empowering the Future of Digital Transformationijtsrd
Artificial Intelligence is not only about the machines that play an authoritative role in humans, but they both are working together. Machines provide the human with the ability of insight and perspective but the machines will not provide the decisive role of supplying judgement and creativity. There is a huge scope of artificial intelligence in this era. The combination of human creativity and technology together results in the excitement that can solve various problems and challenges related to the world. Deepak Kumar "Artificial Intelligence Empowering the Future of Digital Transformation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30287.pdf Paper Url :https://www.ijtsrd.com/computer-science/artificial-intelligence/30287/artificial-intelligence-empowering-the-future-of-digital-transformation/deepak-kumar
What regulation for Artificial Intelligence?Nozha Boujemaa
Should we regulate Artificial Intelligence? What are the challenges to face bias in data and algorithms? What is trustworthy AI? AI HLEG (European Commission) and AIGO (OECD) feedback experiences and recommendations. Example in precision medicine: AI/ML for medical devices
The document discusses the concept of contextual computing and the contextual enterprise. It begins by describing how IBM's Watson system was able to increase the amount of data and metadata available for reasoning by connecting related information and drawing context from existing data, without being connected to the internet. The document then defines contextual computing as applying a similar paradigm of understanding relationships between data and how different processes operate on that data. Finally, it discusses how smart devices can act as natural aggregators of personal context data and how that data can be used to deliver broader contextual applications and services.
The document discusses the concept of contextual computing and the contextual enterprise. It begins by describing how IBM's Watson system was able to increase the amount of data and metadata available for reasoning by connecting related information and drawing context from existing data, even without an internet connection. The document then defines contextual computing as applying a similar paradigm of understanding relationships between data and how different processes operate on that data. Finally, it discusses how smart devices can act as natural aggregators of personal context data like interests, calendars, contacts and location, and how this aggregated data can then be used to deliver broader contextual applications and services.
Similar a Creating Trustworthy AI: A Mozilla White Paper (20)
Ready to Unlock the Power of Blockchain!Toptal Tech
Imagine a world where data flows freely, yet remains secure. A world where trust is built into the fabric of every transaction. This is the promise of blockchain, a revolutionary technology poised to reshape our digital landscape.
Toptal Tech is at the forefront of this innovation, connecting you with the brightest minds in blockchain development. Together, we can unlock the potential of this transformative technology, building a future of transparency, security, and endless possibilities.
Gen Z and the marketplaces - let's translate their needsLaura Szabó
The product workshop focused on exploring the requirements of Generation Z in relation to marketplace dynamics. We delved into their specific needs, examined the specifics in their shopping preferences, and analyzed their preferred methods for accessing information and making purchases within a marketplace. Through the study of real-life cases , we tried to gain valuable insights into enhancing the marketplace experience for Generation Z.
The workshop was held on the DMA Conference in Vienna June 2024.
HijackLoader Evolution: Interactive Process HollowingDonato Onofri
CrowdStrike researchers have identified a HijackLoader (aka IDAT Loader) sample that employs sophisticated evasion techniques to enhance the complexity of the threat. HijackLoader, an increasingly popular tool among adversaries for deploying additional payloads and tooling, continues to evolve as its developers experiment and enhance its capabilities.
In their analysis of a recent HijackLoader sample, CrowdStrike researchers discovered new techniques designed to increase the defense evasion capabilities of the loader. The malware developer used a standard process hollowing technique coupled with an additional trigger that was activated by the parent process writing to a pipe. This new approach, called "Interactive Process Hollowing", has the potential to make defense evasion stealthier.
2. Mozilla Confidential
Agenda
2
Challenges
Challenges accelerated or
deepened by AI.
Introduction
Overview
What are the goals of the
white paper?
Questions
Timeline
Timeline for reviewing and
publishing the paper.
Pathway Forward
Unpacking Mozilla’s AI
Theory of Change.
3.
2.
1.
6.
5.
4.
3. Mozilla Confidential
Shifting
industry
norms
Building new
tech and
products
Generating
demand
1
2
3
Creating
regulations
and incentives
4
Agency
All AI is designed with
personal agency in mind.
Privacy, transparency, and
human well-being are key
considerations.
Accountability
Companies are held to account when
their AI systems make discriminatory
decisions, abuse data, or make people
unsafe.
A
B
3
Overview Introduction Challenges Pathway Forward Timeline Questions
AI Theory of Change
Overview
4. Mozilla Confidential
Why a white
paper?
4
■ Charts the provenance of our ideas and
thinking around AI.
■ Defines Mozilla’s distinct approach to
trustworthy AI.
■ Unpacks Mozilla’s AI theory of change, a
detailed map for our work.
■ Helps us invite others to collaborate and build
off our work. (Partners see Mozilla as a strong
and trusted partner in the AI space).
Overview Introduction Challenges Pathway Forward Timeline Questions
6. Mozilla Confidential
Why Mozilla?
6
■ Mozilla has a rich history of reimagining
computing norms to favor openness and
innovation.
■ Mozilla has historically been a convener of
disparate groups that point towards a
common goal.
■ We’re at an inflection point in the
development of AI that’s not so different
from the early web.
■ Many of the challenges posed by AI are not
new. AI adds a new layer of complexity to key
issues Mozilla has already been working on.
Overview Introduction Challenges Pathway Forward Timeline Questions
7. Mozilla Confidential
Definitions
7
■ AI: The term AI is vague, but has largely come
to represent a broad assemblage of
technologies and techniques.
■ Trustworthy AI: AI that is demonstrably
worthy of trust. Privacy, transparency and
human well-being are key considerations and
there are mechanisms for accountability.
■ Consumer technology: Products and
services used by or purchased by the broad
public. Note: B2B tech or tech used by
governments/law enforcement would fall
outside of this scope.
Overview Introduction Challenges Pathway Forward Timeline Questions
8. Mozilla Confidential
● Industry: Current incentives in the tech industry have resulted in business models that
rely on unfettered access to data. The industry is dominated by a handful of tech giants
who wield immense market and political power.
● Regulators: AI development has largely outpaced regulations, resulting in an
environment where ideas are tested and technologies are deployed to millions of people
without proper oversight or transparency.
● Consumers: People feel increasingly powerless. Consumers do not have the information
they need to make educated choices about which products to purchase or which
platforms to use.
The current state
8
Overview Introduction Challenges Pathway Forward Timeline Questions
10. Mozilla Confidential
Challenges
posed by AI
10
1. Monopoly and centralization
2. Data governance and privacy
3. Bias and discrimination
4. Accountability and transparency
5. Industry norms
6. Exploitation of workers and the
environment
7. Safety and security
Overview Introduction Challenges Pathway Forward Timeline Questions
11. Mozilla Confidential
Companies have a tendency to
stockpile data in order to maintain
their competitive advantage.
Once AI enters the equation,
though, it creates an endless
cycle: Those companies who
dominate the market have greater
access to data, which allows them
to develop better machine learning
models, which enables them to
collect even more data.
1. Monopoly and centralization
11
Only a handful of
tech giants have
the resources to
build AI, stifling
innovation and
competition.
For “platform monopolies” like
Facebook and Google that amass
huge troves of data about how
people behave online, the
competitive advantage is even
more pronounced.
Rapid consolidation of the AI
space is likely to continue, as the
most dominant tech companies
acquire their AI competitors and
the data that comes with them.
Overview Introduction Challenges Pathway Forward Timeline Questions
12. Mozilla Confidential
Privacy concerns intensify with the
development of AI. Vast amounts of
training data (images, text, video, or
audio) are required to teach
machine learning models how to
recognize patterns and predict
behavior.
Machine learning incentivizes
companies to collect user data
without obtaining meaningful
consent and without sufficient
privacy considerations.
2. Data governance and privacy
12
Because AI requires access
to large amounts of
training data, companies
and researchers are
incentivized to develop
invasive techniques for
collecting, storing, and
sharing data without
obtaining meaningful
consent.
As AI continues to drive up the
value of consumer data,
information asymmetry will
continue to increase between
users and the companies
collecting their data.1
Overview Introduction Challenges Pathway Forward Timeline Questions
1
Ginger Zhe Jin, “Artificial Intelligence and Consumer
Privacy,” Working Paper (National Bureau of Economic
Research, January 2018),
https://doi.org/10.3386/w24253.
13. Mozilla Confidential
Every dataset comes with its own
set of biases, and it is impossible to
build a fully unbiased AI system.
Often the bias exhibited in an AI
system is the result of incomplete
or biased training data.
Sometimes the bias in an AI system
occurs when the algorithm
unintentionally latches onto the
wrong things in the dataset to
make predictions.
3. Bias and discrimination
13
AI relies on
computational models,
data, and frameworks
that reflect existing
bias, often resulting in
biased or
discriminatory
outcomes.
Even when steps have been
taken to reduce bias in a model,
that system can still make
decisions that have a
discriminatory effect.
Computer scientists are rallying
around values like “fairness,
accountability, and transparency”
but this perspective often lacks a
justice or equity perspective.
Overview Introduction Challenges Pathway Forward Timeline Questions
14. Mozilla Confidential
Many platforms develop closed
algorithms that rapidly generate,
curate, and recommend content.
Platforms are now in a position
where they are making decisions
that will shape society — and there
isn’t adequate oversight.
So-called “black box” algorithms
defy mechanisms for explainability
and accountability, which is
complicated by the fact that many
corporate algorithms remain
trade secrets.
4. Accountability and transparency
14
Companies often
don’t provide
transparency into
how theirAI systems
work, impairing legal
and technical
mechanisms for
corporate
accountability.
Experts have spent years trying
to boost the overall
interpretability and
explainability of AI — whether a
machine learning system can be
understood by and explained to
a human.
Different methods of building
AI inherently have different
levels of explainability. And
methods for explainability
depend on what kind of
transparency is desired.1
Overview Introduction Challenges Pathway Forward Timeline Questions
1
Andrew D. Selbst and Solon Barocas, “The Intuitive Appeal of Explainable Machines,” SSRN Scholarly Paper (Rochester, NY: Social Science Research
Network, March 2, 2018), https://doi.org/10.2139/ssrn.3126971.
15. Mozilla Confidential
Market pressures — paired with
weak legal limits — has contributed
to a culture in which new products
are not subjected to critical
examination, sufficient testing, or
oversight.
AI is built with a set of assumptions
that have gone unchallenged, and
companies may optimize for a
narrow set of values, such as
profitability, engagement, and
growth.
5. Industry norms
15
Companies are pressured
to build and deployAI
rapidlywithout pausing
to ask critical questions
about the human and
societal impacts. As a
result, AI systems are
embedded with values and
assumptions that are not
questioned in the
development lifecycle.
A real crisis of diversity
(professional, cultural, ethnic,
gender, socioeconomic, and
geographic) contributes to this
problem.
Many engineers, product
managers, designers, and
investors consider
responsibility for AI to be
outside the scope of their job.
Overview Introduction Challenges Pathway Forward Timeline Questions
16. Mozilla Confidential
AI development has spurred
companies to collect increasingly
large amounts of training data,
resulting in unprecedented levels
of energy consumption and
expanding the need for data
centers, which require space and
enormous amounts of cooling
resources.
There is little to no information
about how much energy big tech’s
algorithms consume, but data
suggest the ad tech industry is
the biggest pollutant in this area.
6. Exploitation of workers and the environment
16
The workers who
perform the invisible
work of maintaining AI
systems are particularly
vulnerable. And, the
climate crisis is being
accelerated byAI, which
intensifies energy
consumption and speeds
up the extraction of
natural resources.
Companies building AI-powered
services rely on a vast, invisible
network of on-demand workers
to clean and label datasets, and
to train and improve models.
There are few employment laws
globally that reflect the realities
of the gig economy. This labor is
often precarious and
temporary, with few benefits
or support.
Overview Introduction Challenges Pathway Forward Timeline Questions
17. Mozilla Confidential
Algorithmic curation is
increasingly playing a role in
information warfare as
computational propaganda has
become more sophisticated and
subtle. AI can be used to surface
targeted propaganda,
misinformation, and other kinds of
political manipulation.
Algorithmic curation creates
opportunities for a range of actors
to exploit or “game” those systems
for political and/or financial gain.
7. Safety and security
17
Malicious actors
may be able to carry
out increasingly
sophisticated
attacks by
exploiting the
vulnerabilities of
intelligent systems.
AI can also be used to automate
labor-intensive cyberattacks like
spear phishing, carry out new
types of attacks like voice
impersonation, and exploit AI’s
vulnerabilities with adversarial
machine learning.1
Overview Introduction Challenges Pathway Forward Timeline Questions
1
Miles Brundage et al., “The Malicious Use of
Artificial Intelligence: Forecasting, Prevention,
and Mitigation,” ArXiv:1802.07228 [Cs], February
20, 2018, http://arxiv.org/abs/1802.07228.
19. Mozilla Confidential
AI Theory
of Change
Shifting
industry
norms
Building new
tech and
products
Generating
demand
1
2
3
Creating
regulations
and incentives
4
Agency
All AI is designed with
personal agency in mind.
Privacy, transparency, and
human well-being are key
considerations.
Accountability
Companies are held to account when
their AI systems make discriminatory
decisions, abuse data, or make people
unsafe.
A
B
Overview Introduction Challenges Pathway Forward Timeline Questions
19
20. Mozilla Confidential
1. Shifting industry norms: The people building AI increasingly use trustworthy AI
guidelines and technologies in their work.
2. Building new tech and products: Trustworthy AI products and services are increasingly
embraced by early adopters.
3. Generating demand: Consumers choose trustworthy products when available and
demand them when they aren’t.
4. Creating regulations and incentives: New and existing laws are used to make the AI
ecosystem more trustworthy.
20
AI Theory of Change
Overview Introduction Challenges Pathway Forward Timeline Questions
21. Mozilla Confidential
AI Theory of Change
SHIFTING
INDUSTRY
NORMS
Best practices emerge in
key areas of trustworthy AI,
driving changes to industry
norms.
Engineers, product managers,
and designers with trustworthy
AI training and experience are in
high demand across industry.
Diverse stakeholders —
including communities and
people historically shut out of
tech — are involved in the
design of AI.
There is increased
investment in and
procurement of trustworthy
AI products, services and
technologies.
BUILDING NEW
TECH &
PRODUCTS
More foundational
trustworthy AI technologies
emerge as building blocks
for developers.
Transparency is included as a
feature in more AI enabled
products, services, and
technologies.
Entrepreneurs develop — and
investors support —
alternative business models
for consumer tech.
The work of artists and
journalists helps people
understand, imagine, and
critique what trustworthy AI
looks like.
GENERATING
DEMAND
Trustworthy AI products
and services emerge that
serve the needs of people
and markets previously
ignored.
Consumers are increasingly
willing and able to choose
products critically based on
information regarding AI
trustworthiness.
Citizens are increasingly
willing and able to pressure
and hold companies
accountable for the
trustworthiness of their AI.
A growing number of civil
society actors are promoting
trustworthy AI as a key part
of their work.
CREATING
REGULATIONS &
INCENTIVES
Governments develop the
vision, skills, and capacities
needed to effectively
regulate AI, relying on both
new and existing laws.
Progress towards trustworthy AI
is made through wider
enforcement of existing rules
like the GDPR.
Regulators have access to the
data and expertise they need
to scrutinize the
trustworthiness of AI in
consumer products and
services.
Governments develop
programs to invest in and
incent trustworthy AI.
21
Overview Introduction Challenges Pathway Forward Timeline Questions
22. Mozilla Confidential
AI Theory of Change
22
Overview Introduction Challenges Pathway Forward Timeline Questions
SHIFTING
INDUSTRY
NORMS
Best practices emerge in
key areas of trustworthy AI,
driving changes to industry
norms.
Engineers, product managers,
and designers with trustworthy
AI training and experience are in
high demand across industry.
Diverse stakeholders —
including communities and
people historically shut out of
tech — are involved in the
design of AI.
There is increased
investment in and
procurement of trustworthy
AI products, services and
technologies.
BUILDING NEW
TECH &
PRODUCTS
More foundational
trustworthy AI technologies
emerge as building blocks
for developers.
Transparency is included as a
feature in more AI enabled
products, services, and
technologies.
Entrepreneurs develop — and
investors support —
alternative business models
for consumer tech.
The work of artists and
journalists helps people
understand, imagine, and
critique what trustworthy AI
looks like.
GENERATING
DEMAND
Trustworthy AI products
and services emerge that
serve the needs of people
and markets previously
ignored.
Consumers are increasingly
willing and able to choose
products critically based on
information regarding AI
trustworthiness.
Citizens are increasingly
willing and able to pressure
and hold companies
accountable for the
trustworthiness of their AI.
A growing number of civil
society actors are promoting
trustworthy AI as a key part
of their work.
CREATING
REGULATIONS &
INCENTIVES
Governments develop the
vision, skills, and capacities
needed to effectively
regulate AI, relying on both
new and existing laws.
Progress towards trustworthy AI
is made through wider
enforcement of existing rules
like the GDPR.
Regulators have access to the
data and expertise they need
to scrutinize the
trustworthiness of AI in
consumer products and
services.
Governments develop
programs to invest in and
incent trustworthy AI.
23. Mozilla Confidential
● Dozens of guidelines for “ethical AI” have been published in recent years.
○ Prominent examples: EU’s High-Level Expert Group, the Partnership on AI, the Organization for
Economic Co-operation and Development (OECD), Google, SAP, the Association of Computing Machinery
(ACM), Access Now
● Frameworks agree on several core principles.
○ The most common principles included were transparency (86.9% of frameworks), justice and fairness
(81.0%), a duty not to commit harm (71.4%), responsibility (71.4%), privacy (56.0%), and human
well-being (48.8%).1
● But there are major differences across sectors about what they mean and how they should be
implemented.
○ In their definitions of transparency, nonprofits and governments refer to audits and oversight, whereas
industry refers to technical solutions to transparency, like explainability.
1.1 Best practices emerge in key areas of trustworthy AI, driving
changes to industry norms.
23
1
Anna Jobin, Marcello Ienca and Effy Vayena, “The global landscape of AI ethics guidelines,” Nature Machine Intelligence, vol. 1, no. 9, Sept. 2019, pp.
389–99, https://www.nature.com/articles/s42256-019-0088-2
Overview Introduction Challenges Pathway Forward Timeline Questions
24. Mozilla Confidential
● Engineers and other AI domain experts wield a great degree of decision-making power in
development and deployment of AI systems.
● By supporting education and training in building tech responsibly, we aim to put pressure on
companies seeking to attract top engineering talent.
○ The traditional approach to tech ethics education in CS is far removed from the day-to-day
experience of engineers. A skills-based, situated pedagogy gets students one step closer to
operationalizing trustworthy AI principles in the workplace.
● Crucially, research suggests that the actions of internal advocates won’t have impact unless their
work is aligned with organizational practices.1
1.2 Engineers, product managers, and designers with trustworthy
AI training and experience are in high demand across industry.
24
1
Michael Madaio et al., “Co-Designing Checklists to Understand Organizational Challenges and Opportunities around Fairness in AI,” March 19, 2020,
https://www.microsoft.com/en-us/research/publication/co-designing-checklists-to-understand-organizational-challenges-and-opportunities-around-f
airness-in-ai/.
Overview Introduction Challenges Pathway Forward Timeline Questions
25. Mozilla Confidential
● The diversity crisis in AI has a direct link to problems with bias in AI.
● The teams building AI should strive to reflect the diversity of the people who use the technology,
representing a range of identities, communities, and perspectives.
● Diverse communities should be consulted throughout the AI design and development process.
● Companies must foster an open, transparent culture in which the status quo can be questioned
or challenged without fears of retaliation.
○ In its analysis of the diversity crisis in AI, AI Now concluded that a worker-driven movement
aimed at addressing inequities holds the most promise for pushing for real change in diversity.1
1.3 Diverse stakeholders — including communities and people
historically shut out of tech — are involved in the design of AI.
25
1
Sarah Myers West, Meredith Whittaker, and Kate Crawford, “Discriminating Systems: Gender, Race, and Power in AI,” AI Now Institute,
https://ainowinstitute.org/discriminatingsystems.pdf.
Overview Introduction Challenges Pathway Forward Timeline Questions
26. Mozilla Confidential
● Although there has been a rise in “impact investments” in socially responsible companies and
startups, there is still a lot of work that needs to be done to ensure trustworthy AI products are
getting the funding they need to become viable.
● Tech investors are paying more attention to privacy.
● Tech companies are paying attention to privacy in their acquisition strategy.
● There is a clear opportunity now for such “impact investors” who care about building tech
responsibly to shape the AI product landscape.
1.4 There is increased investment in and procurement of
trustworthy AI products, services and technologies.
26
Overview Introduction Challenges Pathway Forward Timeline Questions
27. Mozilla Confidential
AI Theory of Change
27
Overview Introduction Challenges Pathway Forward Timeline Questions
SHIFTING
INDUSTRY
NORMS
Best practices emerge in
key areas of trustworthy AI,
driving changes to industry
norms.
Engineers, product managers,
and designers with trustworthy
AI training and experience are in
high demand across industry.
Diverse stakeholders —
including communities and
people historically shut out of
tech — are involved in the
design of AI.
There is increased
investment in and
procurement of trustworthy
AI products, services and
technologies.
BUILDING NEW
TECH &
PRODUCTS
More foundational
trustworthy AI technologies
emerge as building blocks
for developers.
Transparency is included as a
feature in more AI enabled
products, services, and
technologies.
Entrepreneurs develop — and
investors support —
alternative business models
for consumer tech.
The work of artists and
journalists helps people
understand, imagine, and
critique what trustworthy AI
looks like.
GENERATING
DEMAND
Trustworthy AI products
and services emerge that
serve the needs of people
and markets previously
ignored.
Consumers are increasingly
willing and able to choose
products critically based on
information regarding AI
trustworthiness.
Citizens are increasingly
willing and able to pressure
and hold companies
accountable for the
trustworthiness of their AI.
A growing number of civil
society actors are promoting
trustworthy AI as a key part
of their work.
CREATING
REGULATIONS &
INCENTIVES
Governments develop the
vision, skills, and capacities
needed to effectively
regulate AI, relying on both
new and existing laws.
Progress towards trustworthy AI
is made through wider
enforcement of existing rules
like the GDPR.
Regulators have access to the
data and expertise they need
to scrutinize the
trustworthiness of AI in
consumer products and
services.
Governments develop
programs to invest in and
incent trustworthy AI.
28. Mozilla Confidential
● A first major step towards better products and services is developing technological building
blocks that can power more responsible AI. These building blocks could include alternative data
governance models, privacy-preserving methods for machine learning, and decentralized, open
source datasets.
● Innovations in privacy-preserving AI include:
○ Edge computing / decentralized computing
○ Federated learning
○ Differential privacy
○ Homomorphic encryption
● Legal innovations in data governance include:
○ Information fiduciaries
○ Data trusts
○ Data co-ops
● And: We need trustworthy pre-trained models & datasets.
2.1 More foundational trustworthy AI technologies emerge as
building blocks for developers.
28
Overview Introduction Challenges Pathway Forward Timeline Questions
29. Mozilla Confidential
● Tech infrastructure:
○ Explainability: The methods used to explain a particular system depend on what kind of
algorithm or ML technique is being used.
○ Auditability: While developers should be regularly auditing their AI systems, they can also
build those systems in a way that makes them easier to audit by third parties.
○ Human-in-the-loop: Human in the loop means that humans are directly involved in
training, tuning, and verifying the data used in an ML system.
● Product design:
○ User control: Platforms and services can be designed in a way that gives users greater
control and agency over the algorithm’s inputs/outputs.
○ Archives/Libraries: Platforms develop transparency products and offerings. This is part of
a broader bulk disclosure demand.
2.2 Transparency is included as a feature in more AI enabled
products, services, and technologies.
29
Overview Introduction Challenges Pathway Forward Timeline Questions
30. Mozilla Confidential
● Companies that demonstrate they care about people’s privacy and well-being increasingly have
a market advantage.
● There is a hunger in the market for different business models that aren’t focused on
aggressively monetizing people’s data.
● Examples of alternative business models:
○ Set up the platform so that people pay to use it.
○ For two-sided businesses, opt to use privacy-preserving methods of doing data analysis.
Offers a new way to identify patterns without exploiting people’s data.
2.3 Entrepreneurs develop — and investors support —
alternative business models for consumer tech.
30
Overview Introduction Challenges Pathway Forward Timeline Questions
31. Mozilla Confidential
● Journalists can serve as corporate watchdogs by investigating computational systems, and they
can also help us understand what is happening by providing context and evidence.
● Artists are exposing the limitations and shortcomings of AI.
○ Artists critique current systems and imagine different ones by providing us a new lens
through which we can see our world.
○ Art is also a speculative tool that helps us see what alternative worlds and technologies
could look like.
2.4 The work of artists and journalists helps people understand,
imagine, and critique what trustworthy AI looks like.
31
Overview Introduction Challenges Pathway Forward Timeline Questions
32. Mozilla Confidential
AI Theory of Change
32
Overview Introduction Challenges Pathway Forward Timeline Questions
SHIFTING
INDUSTRY
NORMS
Best practices emerge in
key areas of trustworthy AI,
driving changes to industry
norms.
Engineers, product managers,
and designers with trustworthy
AI training and experience are in
high demand across industry.
Diverse stakeholders —
including communities and
people historically shut out of
tech — are involved in the
design of AI.
There is increased
investment in and
procurement of trustworthy
AI products, services and
technologies.
BUILDING NEW
TECH &
PRODUCTS
More foundational
trustworthy AI technologies
emerge as building blocks
for developers.
Transparency is included as a
feature in more AI enabled
products, services, and
technologies.
Entrepreneurs develop — and
investors support —
alternative business models
for consumer tech.
The work of artists and
journalists helps people
understand, imagine, and
critique what trustworthy AI
looks like.
GENERATING
DEMAND
Trustworthy AI products
and services emerge that
serve the needs of people
and markets previously
ignored.
Consumers are increasingly
willing and able to choose
products critically based on
information regarding AI
trustworthiness.
Citizens are increasingly
willing and able to pressure
and hold companies
accountable for the
trustworthiness of their AI.
A growing number of civil
society actors are promoting
trustworthy AI as a key part
of their work.
CREATING
REGULATIONS &
INCENTIVES
Governments develop the
vision, skills, and capacities
needed to effectively
regulate AI, relying on both
new and existing laws.
Progress towards trustworthy AI
is made through wider
enforcement of existing rules
like the GDPR.
Regulators have access to the
data and expertise they need
to scrutinize the
trustworthiness of AI in
consumer products and
services.
Governments develop
programs to invest in and
incent trustworthy AI.
33. Mozilla Confidential
● A new market of privacy-forward consumers
○ A new wave of startups whose core focus is bringing technologies like federated learning
into consumer products.
○ Hints that established big tech players want to tap into the market for privacy.
● People who speak non-dominant languages or who use non-Latin characters have historically
been left out of products.
○ Open source initiatives aimed at inclusion and privacy, e.g. Mozilla’s Common Voice
3.1 Trustworthy AI products and services emerge that serve the
needs of people and markets previously ignored.
33
Overview Introduction Challenges Pathway Forward Timeline Questions
34. Mozilla Confidential
● At the moment, consumers don’t feel they can make educated choices about what products to
buy or platforms to use.
● As more products using trustworthy AI reach the market, consumers will need better
information about who and what to trust.
○ Mozilla’s Privacy Not Included
○ Consumer Reports’ Digital Standard
○ Data Nutrition Project
3.2 Consumers are increasingly willing and able to choose
products critically based on information regarding AI
trustworthiness.
34
Overview Introduction Challenges Pathway Forward Timeline Questions
35. Mozilla Confidential
● As we wait for clear consumer protection regulations or a mature market for trustworthy AI
products and services to emerge, consumers will need to pressure companies directly.
● Direct consumer campaigns with precise asks for product changes and transparency is one way
to pressure companies to change their practices.
3.3 Citizens are increasingly willing and able to pressure and hold
companies accountable for the trustworthiness of their AI.
35
Overview Introduction Challenges Pathway Forward Timeline Questions
36. Mozilla Confidential
● Over the last 25 years, a number of public interest organizations have emerged to promote
digital rights and a healthy internet.
● A new crop of AI-focused public interest organizations has also emerged.
● Established, non-tech organizations are getting involved:
○ Increased focus on privacy, data, and AI in traditional consumer rights groups.
○ Increased interest by civil and human rights organizations in the ways in which AI will impact the
communities they serve.
● Building alliances between digital rights groups and groups from other public interest sectors is
likely the most effective way to meet this need.
3.4 A growing number of civil society actors are promoting
trustworthy AI as a key part of their work.
36
Overview Introduction Challenges Pathway Forward Timeline Questions
37. Mozilla Confidential
AI Theory of Change
37
Overview Introduction Challenges Pathway Forward Timeline Questions
SHIFTING
INDUSTRY
NORMS
Best practices emerge in
key areas of trustworthy AI,
driving changes to industry
norms.
Engineers, product managers,
and designers with trustworthy
AI training and experience are in
high demand across industry.
Diverse stakeholders —
including communities and
people historically shut out of
tech — are involved in the
design of AI.
There is increased
investment in and
procurement of trustworthy
AI products, services and
technologies.
BUILDING NEW
TECH &
PRODUCTS
More foundational
trustworthy AI technologies
emerge as building blocks
for developers.
Transparency is included as a
feature in more AI enabled
products, services, and
technologies.
Entrepreneurs develop — and
investors support —
alternative business models
for consumer tech.
The work of artists and
journalists helps people
understand, imagine, and
critique what trustworthy AI
looks like.
GENERATING
DEMAND
Trustworthy AI products
and services emerge that
serve the needs of people
and markets previously
ignored.
Consumers are increasingly
willing and able to choose
products critically based on
information regarding AI
trustworthiness.
Citizens are increasingly
willing and able to pressure
and hold companies
accountable for the
trustworthiness of their AI.
A growing number of civil
society actors are promoting
trustworthy AI as a key part
of their work.
CREATING
REGULATIONS &
INCENTIVES
Governments develop the
vision, skills, and capacities
needed to effectively
regulate AI, relying on both
new and existing laws.
Progress towards trustworthy AI
is made through wider
enforcement of existing rules
like the GDPR.
Regulators have access to the
data and expertise they need
to scrutinize the
trustworthiness of AI in
consumer products and
services.
Governments develop
programs to invest in and
incent trustworthy AI.
38. Mozilla Confidential
● There’s evidence that policymakers are listening to technologists from civil society. But
nonprofits don’t always have the technical capacity and they are often up against tech lobbyists
and experts representing the interests of big tech companies.
● Policymakers are strengthening their capacity by working with more technologists.
○ Emerging field of “public interest tech” has enabled technologists to influence tech policy.
● Some governments are developing AI-specific centers of expertise.
● Areas to invest:
○ Expanding cross-disciplinary university programs that combine public policy and tech, and
growing the number of research institutions with a focus on AI
○ Creating centers of tech expertise that can be used across departments
4.1 Governments develop the vision, skills, and capacities needed
to effectively regulate AI, relying on both new and existing laws.
38
Overview Introduction Challenges Pathway Forward Timeline Questions
39. Mozilla Confidential
● Governments are working together to develop global governance frameworks for AI.
○ In 2019, 42 countries took a critical step when they came together to endorse a global
governance framework on AI, the OECD AI Principles.1
The G20 adopted a set of global AI
Principles, largely based on the OECD framework.
● At the same time, countries are putting together their own governance frameworks.
○ European Commission’s 2020 White Paper
○ UK Lords Select Committee’s 2017 AI guidelines
○ China’s 2019 Governance Principles for Responsible AI
○ Singapore’s 2020 Model AI Governance Framework
● The EU’s vision is the most mature. But there’s a gap: The EU has yet to consider the use of AI in
consumer technologies as “high risk”, despite the fact that such technologies pose major
collective risks.
39
Overview Introduction Challenges Pathway Forward Timeline Questions
4.1 Governments develop the vision, skills, and capacities needed
to effectively regulate AI, relying on both new and existing laws.
40. Mozilla Confidential
● Existing laws and regulations that protect data rights can be wielded in a meaningful way to
address many of the challenges outlined in this paper.
● Existing privacy laws like the GDPR
○ The GDPR has been used to pressure companies into taking data security seriously and to
tackle the surveillance economy and rampant data collection that powers AI.
○ But there are parts of the GDPR that apply to AI that have not yet been tested
■ Article 22: “Automated individual decision-making, including profiling” - mandates that AI cannot
be used to make decisions that have significant impact AND affirms a ‘right to explanation’
■ Article 5: “Principles Relating to Processing of Personal Data” - requires that data processing is fair
AND affirms the principle of data minimization
■ Article 35: “Data Protection Impact Assessment” - requires data protection impact assessments.
4.2 Progress towards trustworthy AI is made through wider
enforcement of existing laws like the GDPR.
40
Overview Introduction Challenges Pathway Forward Timeline Questions
41. Mozilla Confidential
● Antitrust law
○ Antitrust laws could be applied to break up monopolies in the tech industry, which would
help spur competition and innovation in AI.
○ In the EU, authorities have not shied from imposing fines on big tech companies based on
competition law.
○ In the U.S., a renewed interest in antitrust laws among legal scholars and regulators has
presented an opportunity to strengthen competition policy.
4.2 Progress towards trustworthy AI is made through wider
enforcement of existing laws like the GDPR.
41
Overview Introduction Challenges Pathway Forward Timeline Questions
42. Mozilla Confidential
● Full transparency has limitations: it often ignores systems of power, obscures itself further by
overwhelming people, and can promote a false sense of knowledge.1
● Transparency in this context could mean many things:
○ Source code / open source
○ Training data documentation
■ A comprehensive list of all the datasets used, an assessment of the quality of the datasets, an
explanation of how the datasets were manipulated, any records of possible sources of bias, and a
plan for how to account or correct for that bias.
○ AI documentation
■ The model’s training methods, processes and techniques used to test and validate the AI, what
values the model is optimizing for, weights for each parameter at the outset, etc. Should also
include normative explanations for why a particular method was chosen.
○ Data archives/APIs (see 2.2)
4.3 Regulators have access to the data and expertise they need to
scrutinize the trustworthiness of AI in consumer products and
services.
42
1
Mike Ananny and Kate Crawford, “Seeing without Knowing: Limitations of the Transparency Ideal and Its Application to Algorithmic Accountability,”
New Media, Dec 13, 2016, https://doi.org/10.1177/1461444816676645.
Overview Introduction Challenges Pathway Forward Timeline Questions
43. Mozilla Confidential
● Governments are developing industrial policy that matches their policy goals and vision for AI.
● Governments are developing a procurement strategy that matches their strategic vision for AI.
○ Cities Coalition for Digital Rights
○ UK’s “Guide to using AI in the Public Sector”
● Government agencies adopt procurement guidelines directly into the terms and conditions of
vendor contracts.
4.4 Governments develop programs to invest in and incent
trustworthy AI.
43
Overview Introduction Challenges Pathway Forward Timeline Questions