2. Cognitive Technologies do not eliminate jobs
• The most suited automation approach is called empower, or
augment. In this approach to automation the focus is making the
geoscientist more effective, possibly by automating what wasn’t
even being done before.
• This can help geoscientists make more informed decisions than
before.
• The augmentet approach to automation appeal most to knowledge
workers.
3. Automation mostly goes at geological task level
and not entire geoscientific job
• Replace strategy is not the most popular option. Atomize and
then automate is far more common.
• For knowledge workers like geoscientists are, empowerment or
augmentation is generally a good strategy
• You have a whole set of processes within the geoscientific work
that can be automated or augmented to some degree
4. Besides automation choices, implementing
cognitive technologies, strategic choices has to
be made
• Choice is between a Cost strategy and/or a Value strategy.
• A cost strategy uses technology to reduce costs, especially by reducing
amount of specialists but also possibly by reducing errors and rework.
• A value strategy increases value by using technology to make
geoscientists more effective and more productive or by reassigning
geoscientists to higher value work as technology automates lower value
work.
• Neither the task nor the technology used nor the automation approach
dictate whether to follow a cost strategy or a value strategy.
5. Value rather than Cost Strategy?
• Prefer the value approach but is is a harder sale.
• It takes more creativity.
• It takes more careful thought about how to deliver more value with cognitive
technologies.
• Most organizations will try the cost strategy, which can be self-limiting as they lead to
commoditization.
• Commoditization lend more to service providers to promote products, rather than create
an advantage to your own organization, only known to yourself and no one else.
• Everybody in the industry adopts the same kinds of cost reducing automation then your
organization do not have any advantage anymore.
• A Deloitte study has shown actually that over a long period of time value creation tends
to produce higher performance for companies rather than just focusing on cutting costs.
6. Choices of Automatization and Strategies
• Cognitive technologies present:
• four automation choices and
• two strategy choices.
• There’s no unique solution of choices for organizations to make,
but organizations will have to make choices rather than assume
that there’s only one way to use cognitive technologies to
empower the geoscientist in his work.
7. Geoscientific Product Applications
of Cognitive Technologies
• Embed cognitive technologies in a geoscientific product or service
which delivers a benefit to the geoscientist and its company.
• Main purpose it to create value for the company with cognitive
technologies
• Greater ease of use and convenience trough automating processes and tasks
which are repetitive and does not require high skillsets to perform.
• Simplicity through learning the preferences in a certain geological task or
process allowing to eliminate use of knobs, settings, and dials and let a
product figure out on its own what you want.
• Empowering and instilling confidence in the geoscientist, especially when
they have to make complex decisions, like making choices which could be
based on prior experiences and choices made in similar situations.
• Emotional effects through being able to communicate with the product in a
way that creates emotional bonds between geoscientist and product used.
8. Geoscientific Process Applications
of Cognitive Technologies
• These are applications that use cognitive technologies to automate tasks or
business processes internal to an organization.
• development of algorithm for preventive maintenance or standard tasks to be performed
routinely, that automatically creates an optimal schedule saving days of planning work per
week and allowing geoscientist to spend time on other priorities. Automating expert decisions.
• processing massive amount of geoscientific and engineering related documents per month,
many handwritten. Facing deadlines to use this data encourage the organization to deploy an
automated handwriting recognition system coupled with human oversight to ensure quality
enables geoscientists to scale up and handle the volume of data available to them. Relieving
skilled workers of unskilled tasks.
• Screening of analysis results, some in free form notes, others in various format reports and
other in image formats, utilizing natural language processing combined with image processing
system to refine the list of terms extracted from this data to automatically suggest what cases
are worth following up on. Relieving skilled workers of unskilled tasks.
• The benefits of process applications are getting work done faster, cheaper,
better or some combination of these.
9. Geoscientific Insight Applications
of Cognitive Technologies
• analyzing large amounts of data including unstructured data such as text or
images to discern patterns or make predictions.
• a predictive algorithm that automatically classifies plays/ traps into categories that are likely
to have similar success rates or stratigraphic patterns or combinations of other vital factors
deemed to be of importance for plays/ traps.
• use of natural-language-processing system to track and understand what other
scientists are saying about the company and its competitors online.
• identify salient topics of scientist’s chatter and the sentiments surrounding those topics. The
insights delivered by the system influence decisions on insentives, compensations, working
methodologies , on perks and how company reps should respond to certain inquiries about
work and compensations.
• develop a machine-learning application focused on specific geoscientific
challenges or topics, which could increase chance of success of certain
geological problems.
• Using data from research reports, studies, client produced data etc., predicts the probability
pf developing success cases and reduce the costs identifying these.
10. Geoscientific Insight Applications
of Cognitive Technologies
• Insight applications make entirely new kinds of analysis possible.
• The benefits of insight applications are better and faster decisions that can
improve operating and strategic performance.
• You would benefit from Geoscientific Insight application of Cognitive technology
when you have large data sets that have not yet been fully analyzed or
unstructured data sets that couldn’t have been analyzed using traditional
techniques and look for processes where the value of improved performance is
high.
• Geoscientific Insight applications involve analyzing large amounts of data and
using the analysis to discern patterns or make predictions.
• Machine learning is a key cognitive technology here.
• The benefits can be better decisions and better operational performance.
11. Geoscientific Applications
of Cognitive Technologies
• Cognitive technologies can handle knowledge representation and reasoning, learning,
perception and physical action.
• There are three types of applications of cognitive technologies: product, process and
insight.
• Start evaluating these technologies now to make your staff more efficient now.
• Know that there are choices to make about whether and where to apply them and what
and how much to automate it and also whether to pursue a cost or a value strategy.
• Identify how to take advantage of cognitive technologies to do better geoscientific work
more efficiently.
• Identify skills you’ll need in your organization and never stop developing them to
develop cognitive systems for use in geoscientific purposes.
12. Next wave of Geoscientific Cognitive
Applications
• Personalized and learning to adapt themselves to personal geoscientist needs.
• Neuromorphic Computing, Quantum computing utilizing AI technology through smaller
computers with more power and abilities using less energy to run. This will enable the
computers to become an extension to the geoscientists brain. Form factors comes into
play here, which can allow us to take advantage of opportunities through smaller devices
in embedded applications. F.inst., if we want to put high power/ ability very small
sensors on the seafloor or on the surface at land to perform measurements of important
variables required by the geoscientist and/ or engineers. These will be cheap computing
devices working within collaboration with each other and learn by its own observations
and from from each others observations and perform analysis.
• Faster and richer amount of data will require decision making and analysis as data is
acquired by the sensors. Internet of Things (IoT) combined with a Big Data challenge.
• Data mining beyond human capabilities to identify patterns and connections.
13. Stig Arne Kristoffersen, Valioso Ltd
https://uk.linkedin.com/in/stigarne
http://www.Valioso.rocks
https://twitter.com/ukranova
