How Experts Think

We captured expertise from observations, then linked it with neural networks.

Eye Tracking During Building Inspections Provides Insight on How Experts Think   By Penn State News,   March 30, 2023

Penn State's Maria antonieta Gutierrez Soto uses Tobii eye-tracking glasses to assess damages in row buildings in Mayfield, Kentucky after the region endured tornadoes in December 2021.

Researchers at Pennsylvania State University (Penn State) and Chariho Regional High School in Rhode Island used eye-tracking software to analyze building inspectors' gaze patterns to gain insights into safety assessment behaviors.

The researchers had architectural engineering graduate students evaluate two building facades while tracking their gaze with Tobii glasses, which measure eye movement and positioning concurrently.

Penn State's Rebecca Napolitano said the results reflected users' biases when looking at structures, and a tendency to focus on observable issues longer compared to other fields.   She called the research "one small step in understanding how inspectors think, with the long-term goal of creating an algorithm to inform a drone."

From Penn State News

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Emerging AI Attached to Business Meetings and Process Management.

Some of the work we did in the enterprise a dozen plus years ago was to improve executive decision making based on visualized data.   Especially useful when it needed to focus complex, expensive  and difficult to obtain expertise.    And results that further need to be linked to known and developing process.  At the time we were also working with strategic AI approaches, but it had yet to mature.   It comes to mind now that methods like GPT make this easier, especially when integrated with data visualization and large data base exploration.     Exploring further .... 

Here is a set of posts:   from this blog about the work then.  

Connect to discuss ...     Franz   

Managing Knowledge, GPT towards a Killer Use case?

Sounds like the 'expert systems' of days past, we wrote a number in various contexts.  Results I have seen now are still shaky, often easy ridiculed, but still approaching real possibilities. 

Right now there is no “killer” use case for using ChatGPT in the enterprise — that is, one that will have an enormous impact on the top and the bottom line — according to EY’s global chief technology officer, Nicola Morini Bianzino. 

But that could soon change: The next six to 12 months will bring an explosion of experimentation, he predicted, especially once companies are able to build on top of ChatGPT using OpenAI’s API. And the killer use case that emerges could be around generative AI’s impact on knowledge management — that Bianzino describes as the “dialectic of AI.” 

Up Next

“Knowledge companies tend to store knowledge in a very flat, two-dimensional way that makes it difficult to access, interact and have a dialogue with,” he told VentureBeat in an interview. “We tried 20, 30, 40 years ago to build expert systems. That didn’t go really well because they were too rigid. I think this technology promises to overcome a lot of issues that expert systems have.”

As ChatGPT and similar tools evolve and improve, and can be trained on an enterprise’s data in a secure way, it will change the way we access and consume information inside the enterprise, he explained.   ... '

Lowe's Goes Virtual for Pro Home Improvement

Most intrigued about how the knowledge is being stored, delivered,utilized.      There are different levels of expertise embedded in 'Pro', so will this context be included?   Ultimately essentially.

Lowe’s ‘virtually’ goes on the job for home improvement pros   by George Anderson in Retailwire

Lowe’s is introducing a new tool that will enable carpenters, electricians, plumbers and other construction professionals to meet with customers to discuss projects without having to go to their homes.

Lowe’s for Pros JobSIGHT makes use of video, computer vision and augmented reality tech to help pros evaluate projects so they can provide quotes to consumers on a wide variety of repair and home improvement projects. Pros using the tool chat directly with homeowners and are able to conduct tasks, such as determining product serial numbers and product details. They can use an on-screen laser pointer and augmented reality quick-draw tools to work through the consultation with homeowners. When the virtual meeting is complete, pros receive a one-page summary including video and audio, hi-res photos and notes for follow-up.

Lowe’s is making Pros JobSIGHT free to trade professionals through Oct. 31. Those who sign up for the program also save five percent on the chain’s everyday prices and are eligible for zero-interest purchases using their business accounts with Lowe’s. Extended payment terms are also available.  ... '

Using Business Rules and Expertise

Via DSC, what looks to be a good podcast on this topic.  It has been a favorite approach of mine since the beginning.  Narrow machine learning methods can be very valuable, but to deliver them they have to be part of existing or proposed tasks or businesses.  Operationally embedded.   That requires real-life decision rules.  Access information to the podcast at the link below.  More on this topic to follow. 

Data Science Fails: Ignoring Business Rules & Expertise 

Nowadays, we have unprecedented access to data, plus the computing power and advanced algorithms to find correlations. We look at a cautionary case study of a cancer center that embarked on an ambitious plan to use AI to eradicate cancer. When AI is being asked to make decisions with significant consequences, such as life and death healthcare recommendations, it needs to be trustworthy. But if you don't follow best practices, if you don't include the knowledge of subject matter experts, and if you don't enforce business rules, your AI project will not be successful.

In this latest Data Science Central podcast, learn four AI governance practices that can help you achieve AI success.

Speaker: Colin Priest, VP of AI Strategy - DataRobot
Hosted by: Sean Welch, Host and Producer - Data Science Central .... 

Embedding Human Expertise

Useful examination of delivering expertise, human and otherwise.

Crate and Barrel marries human expertise with tech advances in a new concept store   by Matthew Stern

Crate and Barrel is piloting a standalone store concept that lets customers take advantage of all of their design and decorating expertise and guidance in one physical location.

Crate and Barrel opened its first Design Studio at the end of January in Pasadena, CA, according to the Pasadena Star News. The new location brings the online experience of Crate and Barrel’s design services to its own store, where customers can get specialized help from experts on how to decorate rooms from the ground up, using 3-D renderings and choosing from furniture and décor. The store will have items not available at other Crate and Barrel locations and will also allow visitors to choose custom and made-to-order furniture.  ....  "

Imposter Syndrome and the Turing Test

How a Famous Robot Test Can Help You Beat Impostor Syndrome  by Kelton Reid in Copyblogger

Points to a 2012 Atlantic article on using the Turing Test to discern (or fool) people, or even ourselves into determining who we are.   Fascinating piece,  especially with regard to how an intelligent dialog is considered part of the test process.  Which is different than just asking a question and determining if people can answer it correctly.  Its not just what you know, but how you can adjust that knowledge to contextual needs.    Also harder for AI to reproduce.

" ... In the words of sociologists, what they're now studying is called "interactional expertise." The easiest way to understand what interactional expertise entails is to contrast it with a more common idea, contributory expertise. Contributory experts are the typical array of professionals (physicists, chemists, lawyers, economists, musicians etc.) who develop specialized knowledge and skill through formal education and long experience. ... "  

AI Building AI

It has been long suggested that this would occur.  This is still relatively hard, but we have seen apps like Watson Analytics show how it could be done.  Though that is about data science, and this further embodies the logic and process of AI.  In Technology Review:

 AI Software Learns to Make AI Software
Google and others think software that learns to learn could take over some work done by AI experts.
by Tom Simonite .... "

Knowledge Explosion in Medicine

Good detailed piece.  Many industries and companies are dealing with explosions of information and data that need to be understood and integrated into current process.  Mentions such efforts as Watson in medicine.  Also how will current human expertise be integrated with incoming learning?   Big challenges all around to make these approaches sustainable though maintenance and curation.

How Physicians Can Keep Up with the Knowledge Explosion in Medicine
by Lynda Chin and Greg Satell

" .... However, such reliance on manual curation creates not only a scale problem but also quality and consistency challenges. With the arrival of more advanced analytics such as IBM Watson, we can imagine more intelligent system such as MD Anderson’s Oncology Expert Advisor that one of us (Lynda) previously developed. It combines human expertise with machine learning to synthesize a large knowledge base in cancer and suggests treatment options tailored to a specific patient in real time. This will help doctors make better decisions based on up-to-date knowledge in a time efficient manner. .... " 

Neural Networks and Complex Reasoning

Beyond just recognition, on to recognizing and reasoning.  Like to see this in a business context that includes complex quant optimization.  Some of our own experiences typically built a representative quant model, then had humans do the associated reasoning and 'fuzzy' decisions.  Crowd sourcing the logic among experts.  The external memory represents a context?  Will this take deep learning beyond?

Google's AI Reasons Its Way Around the London Underground    in Nature

Artificial-intelligence systems known as neural networks can recognize images, translate languages and even master the ancient game of Go. But their limited ability to represent complex relationships between data or variables has prevented them from conquering tasks that require logic and reasoning. ...

In a paper published in Nature on 12 October, the Google-owned company DeepMind in London reveals that it has taken a step towards overcoming this hurdle by creating a neural network with an external memory. The combination allows the neural network not only to learn, but to use memory to store and recall facts to make inferences like a conventional algorithm. This in turn enables it to tackle problems such as navigating the London Underground without any prior knowledge and solving logic puzzles. Though solving these problems would not be impressive for an algorithm programmed to do so, the hybrid system manages to accomplish this without any predefined rules.

Although the approach is not entirely new — DeepMind itself reported attempting a similar feat in a preprint in 2014 — “the progress made in this paper is remarkable”, says Yoshua Bengio, a computer scientist at the University of Montreal in Canada. .... "

Towards Multi-Step Expert Advice for Cognitive Computing

Dear Professors, Students, IBMers and others, 

This a reminder about our Cognitive Systems Institute Group Speaker Series this week, Thursday, October 13, 2016 at 10:30 am ET US (7:30 am PT and 4:30pm in Germany). Our presenter is Achim Rettinger from Karlsruhe Institute of Technology, who will be presenting “Towards Multi-Step Expert Advice for Cognitive Computing.”

Please point your web browser to https://apps.na.collabserv.com/meetings/join?id=2894-8491  password=cognitive. Use audio on computer or dial 855-233-7153 in the US (other countries numberhere) PIN Code: 43179788   Non-IBMers please use the "guest" option instead of entering your email.   

For slides and talk recording.
For Discussion afterwards. 

Thank you and please let me know if you would like to be a presenter on an upcoming call! 

Also, I want to let you know about two upcoming conferences: World of Watson in Las Vegas starting with an Academic Workshop in Cognitive and Data Science on October 23 (Conference 10/24-27) and Educause in Anaheim, CA October 25-28. Also, I am organizing a Cognitive Tutorial at the HICSS Conference in Hawaii, January 4 (Conference 1/4-1/7/17). Let me know if you would like more information on registration costs and agendas. 

Dianne Fodell

IBM Global University Programs
fodell@us.ibm.com

Why and How is Watson a Cognitive System?

Jim Spohrer sends along a link to a talk by Rob High, IBM Chief Technology Officer, Fellow and Vice President,  Does a good job of discussing why Watson is cognitive, unique, and why it differs from previous attempts at delivering expertise.   Non technical.

I ask: So how you convince a complex organization this uniqueness is useful, stable and scalable? Only through clear operational examples in varying contexts.  That appears to be what they are working on.

Abstract

IBM® Watson™ represents a first step into cognitive systems, a new era of computing. Watson builds on the current era of programmatic computing but differs in significant ways. The combination of the following capabilities makes Watson unique:

Natural language processing by helping to understand the complexities of unstructured data, which makes up as much as 80 percent of the data in the world today

Hypothesis generation and evaluation by applying advanced analytics to weigh and evaluate a panel of responses based on only relevant evidence

Dynamic learning by helping to improve learning based on outcomes to get smarter with each iteration and interaction

Although none of these capabilities alone are unique to Watson, the combination delivers a powerful solution:

To move beyond the constraints of programmatic computing
To move from reliance on structured, local data to unlock the world of global, unstructured data
To move from decision tree-driven, deterministic applications to probabilistic systems that co-evolve with their users

To move from keyword-based search that provides a list of locations where an answer might (or might not) be located, to an intuitive, conversational means of discovering a set of confidence-ranked responses

This IBM Redguide™ publication describes how Watson combines natural language processing, dynamic learning, and hypothesis generation and evaluation to give direct, confidence-based responses.

For additional information about how Watson can transform how organizations think, act, and operate in the future, see the IBM Redbooks Point-of-View publication "Transforming the Way Organizations Think with Cognitive Systems", REDP-4961:

Table of contents:
What language is and why it is hard for computers to understand
IBM Watson understands language
Understanding language is just the beginning
Problems come in different shapes
Accuracy is improved through generalization  ... 

Convetit: Real Time Problem Solving Dialog

I recently participated in a forum on AI/Cognitive applications.

Convetit: 
" ...  Powered by an open platform of real world problem solvers, Convetit brings professionals together for intense dialogues in online moderated engagements. These hands-on experiences provide an unbiased view into where markets and solutions are headed next. Pivot faster than your competition and get breakthrough perspective with curated teams of experts, on demand. ... " 

Their blog.   Contains some interesting problem solving and innovation case studies.

Robots in the Retail Aisle at Lowe's

Lowes has long been a great experimenter in technology space.  But what has lasted?   Naturally, since it needs expertise to be delivered in a very complex aisle.  Good piece further, about the retail presence of robotics.  In K@W: 

Robots in Aisle 10: Will Shoppers Like Them?

This fall, customers cruising the aisles of Lowe’s home improvement stores in the San Francisco Bay Area may see a new type of employee taking inventory and assisting shoppers. You won’t find a nametag on this worker, but you won’t confuse it with other employees, either. The new kid in town is the LoweBot, an autonomous retail service robot that scans and audits store inventory on the floor. It uses voice recognition to identify products for customers and lead them to the right shelf — in multiple languages.

The retailer is deploying LoweBots at 11 of its Bay Area stores over a seven-month period using NAVii robots made by Fellow Robots, following a successful two-year pilot program of a first-generation robot called OSHbot that was tested at one of Lowe’s Orchard Supply Hardware stores. .... " 

Lowes Innovation Labs.

Critical Importance of Subject Matter Experts

Absolutely.  I usually call it context understanding.  And that  understanding comes from having subject matter expertise close at hand.   In Information Management.  " .... "Know thy self, know thy enemy" says Sun Tzu in 'The Art of War'. Creating a domain/data model and relying on subject matter experts throughout the development of the ML system will certainly guarantee you a success. And finally, your product, albeit highly specialized, will not be a threat to the domain experts, but rather a natural extension of their abilities. True experts cannot be substituted. ... " 

Enterprise Ontology Frameworks

An investigation brought this to my attention.  Ontologies can give organization to many kinds of analytics processes.

The Enterprise Ontology Reference Framework
The Global University Alliance (GUA) is an open group of academics with the ambition to provide both business and academia with state-of-the-art insights. Through its ties with the LEADing practice community, which includes large firms and governments, the GUA is able to evaluate and valorize its scientific output. Since 2004, the members of the GUA strive for a continuous improvement of their expertise through the research, comparison, analysis and development of Best and LEADing Practices in Business. Throughout this process, the GUA built its own implicit ontology that revolves around its expertise of Best and LEADing practices.

As ontology formally represents knowledge as a set of concepts within a domain, and the relationships between those concepts, it can be used to model a domain and support reasoning about concepts. The Global University Alliance has used the concept of ontology as both a shared vocabulary and the very definition of its objects and concepts. In order to go the next steps and fully use the potential of its ontology. .... " 

Automating Data Science

In the DSC:

Data Scientists Automated and Unemployed by 2025!
Posted by William Vorhies

Summary:  The shortage of data scientists is driving a growing number of developers to fully Automated Predictive Analytic platforms.  Some of these offer true One-Click Data-In-Model-Out capability, playing to Citizen Data Scientists with limited or no data science expertise.  Who are these players and what does it mean for the profession of data science? ... " 

AI for High Frequency Trading

Via the Financial Revolutionist:

Note the statement that this simulates the insights of experienced traders.   So more of an expertise based system rather than a machine learning approach?  Likely some combination of the two. Which brings together business process knowledge and deep analytics.   An ideal mixture!

Securities Houses turn to AI for High-frequency trading
 In the age of ultra-high-frequency trading, financial institutions are turning to artificial intelligence to improve their stock trading performance and boost profit.

     One such company is Japan's leading brokerage house Nomura Securities. The company has been pursuing one goal: to simulate the insights of experienced stock traders with the help of computers. After years of research, Nomura is set to introduce a new stock trading system for institutional investors in May. ... " 

A Menu Collection

An example of crowdsourcing and identifying complex data.  Or consider a menu a kind of expertise presentation.

Help The New York Public Library improve a unique collection!
We’re transcribing our historical restaurant menus, dish by dish, so that they can be searched by what people were eating back in the day. It’s a big job so we need your help! Learn more. ...  " 

And in the library blog. 

Automating Proof

In the first wave of AI considerable attention was paid to the concept of 'automating proofs'.  With the idea that we could take rules about expertise,  and then combine and extend them to provide deeper insight into business decisions.  In general this did not work for business decisions.  Nor does this automating process add to that goal.