C. Education for harnessing AI technologies
(RFI question 7)

Last updated July 28, 2016

The potential for AI solutions for public and private uses has created a fast growing demand for AI skills. To meet this demand, top universities are crafting new AI curricula. Leading firms offer faculty and students access to cloud platforms with AI-based services, from image recognition to machine learning. However, most courses and platforms require programming skills and advanced mathematics as prerequisites. Government agencies, research institutions, universities, and foundations can work together to make learning to build, understand, and work with AI systems more accessible to a broader range of students and professionals retooling their careers.

Online courses and competition for talent: Faculty, students, and industry professionals are retooling their skills. Lists of online courses in AI and cognitive systems have been compiled and continue to grow. Top universities report record enrollments in their online AI courses. In partnership with Udacity, Coursera, or EdXor, others, offer these courses to learners globally, not just students at their university. In the short-term (five years), the industry will compete fiercely for top AI faculty and students. News stories abound as firms acquire top academic talent in areas such as driverless cars and deep learning. In the longer-term (ten years), data eats software - meaning the focus will be less on faculty and students who know specific AI algorithms and more on faculty with reputations around unique data sets and decision making expertise. Over time, algorithms mature and become "good enough" for industry level applications. Data sets and expertise increasingly become what industry seeks for competitive advantage. Some companies with lots of data and software are providing open access to key algorithms to build skills.In sum, learners can access many online artificial intelligence related courses, including Udacity, Coursera, or EdXor. In addition, headlines tell the story about the war for talent for driverless cars and deep learning experts, including faculty and students.

Industry platforms: Industry is competing to provide faculty, students, entrepreneurs, and developers access to cloud platform with cognitive services for skills development and startups. These cloud platforms for cognitive solutions are the factories of the 21st century - and employees and customer compete to demonstrate the value of the platforms to co-create value with others while solving personal, business, or societal challenges. Regional economic development groups and universities are increasingly interested in developing entrepreneurial students to launch AI powered startups. Because in many cases, university academic disciplines map directly to occupations, the faculty and student expertise can be directly useful to startups that build cognitive tools and assistants for use by workers in all occupations (see O*NET online).

Non-programmer and multidisciplinary access: More inclusive courses are needed to help student learn to build, understand, and work with AI systems. Because of the excellent technical online courses for AI, there is no shortage of access to introductory training and curriculum for students with computer science, programming skills, and advanced mathematics prerequisites. However, a shortage is curriculum for non-technical users, curriculum that integrates computer science with artificial intelligence, cognitive science with AI and cognitive architectures, and neuroscience; open data sets for testing machine learning algorithms on societally meaningful tasks; and open tool kits that allow learners to build their own AI mediator systems to process their emails and interact with the cognitive mediators of others, open business models and economic models for combining the best AI components for new applications. Next generation university curriculum should have four tracks: for researchers, entrepreneurs, practitioners, and citizens. Building, understanding, and working with cognitive systems is important and should be accessible to everyone. There is growing awareness of new types of skillsets and mindsets for leadership, innovation, and management.

Institutional collaborations and project focus: Organizations can collaborate on a framework for the development of cognitive assistants for all occupations. O*NET (the online occupation database network) was established by the US Department of Labor, and now is an open data set that maps the changing natures of occupations across the economy. From accountants to zoologists, all disciplines across management, science, engineering, law, health care, and the arts are represented in this list of occupations that people fill in our American economy. AI systems that help people do more with big data is in fact a people-centered system redesign approach for cognitive assistance for all occupations. This type of system redesign requires understanding the interactions between people in various occupations, and the role cognitive assistants can play in improving the creativity and productivity of those occupation-to-occupation and employee-to-customer interactions, not just the tasks within an occupation. For example, IBM piloted a Cognitive Build initiative for all employees to collaborate in envisioning their transformed job roles in the cognitive era. As data becomes the most abundant and valuable natural resource, mining it for insights will become an aspect of all knowledge-worker jobs. Professional associations can play a role in helping industry competitors collaborate with universities and government on these important issues

In sum, to keep up with the demand for new skills, online AI courses are available from a number of top universities. In addition, leading firms offer faculty and students access to cloud platforms with AI services, from image recognition to machine learning. However, most courses and platforms require computer science, programming skills, and advanced mathematics as prerequisites. Furthermore, the available data sets are not sufficiently developed to fully engage the full range of diversity in the backgrounds of students and practitioners. Truly multidisciplinary, multisector, and multicultural approaches are nascent at best. Government agencies, research institutions, universities, and foundations can work together to make it easier for learning opportunities to focus on the development of cognitive systems for all occupations and societal roles. Projects should align to help people learn to build, understand, and work with cognitive systems to deal with information explosion. Organizations should enable employees and customers to re-imagine their roles and value co-creation interactions in the cognitive era.

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