“Working with AI: Real Stories of Human-Machine Collaboration” with Professor Thomas Davenport and Professor Steven Miller

Working with AI Reviewed at Bridging the Gaps

There is a widespread view that artificial intelligence is a job destroyer technical endeavour. There is both enthusiasm and doom around automation and the use of artificial intelligence-enabled “smart” solutions at work. In their latest book “Working with AI: Real Stories of Human-Machine Collaboration”, management and technology experts professor Thomas Davenport and professor Steven Miller explain that AI is not primarily a job destroyer, despite popular predictions, prescriptions, and condemnation. Rather, AI alters the way we work by automating specific tasks but not entire careers, and thus freeing people to do more important and difficult work. In the book, they demonstrate that AI in the workplace is not the stuff of science fiction; it is currently happening to many businesses and workers. They provide extensive, real-world case studies of AI-augmented occupations in contexts ranging from finance to the manufacturing floor.

In this episode of Bridging the Gaps I speak with professor Thomas Davenport and professor Steven Miller to discuss their fascinating research, and to talk through various case studies and real work use cases that they outline in the book. We discuss the impact of Artificial intelligence technologies on the job market and on the future of work. We also discuss future hybrid working environments where AI and Humans will work side by side.

Professor Thomas Davenport is a Distinguished Professor of Information Technology and Management at Babson College, a visiting professor at the Oxford University and a Fellow of the MIT Initiative on the Digital Economy. Steven Miller is Professor Emeritus of Information Systems at Singapore Management University.

We begin our discussion by looking at various aspects of the environments where AI and human workers work side by side, and then discuss the concept of Hybrid Intelligence. Then we talk about the challenges that organisations are faced with while developing and implementing Artificial Intelligence enabled technologies and solutions in enterprise environments. An important question that I raise during our discussion is, are the organisations ready for large scale deployment of AI solutions. The book is full of real world case studies and covers a wide variety of use cases. We delve into a number of these real world case studies and use cases. This has been a very informative discussion.

Complement this discussion with “The Technology Trap” and the Future of Work” with Dr Carl Frey and then listen to “Machines like Us: TOWARD AI WITH COMMON SENSE” with Professor Ronald Brachman

By |October 31st, 2022|Artificial Intelligence, Computer Science, Future, Podcasts, Technology|
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“Machines like Us: TOWARD AI WITH COMMON SENSE” with Professor Ronald Brachman

Machines Like us reviewed on Bridging the Gaps

There is a consensus among the researchers in the field of artificial intelligence and machine learning that today’s artificial intelligence systems are narrowly focused, are designed to tackle specialised tasks and cannot operate in general settings. An important feature of the human brain that enables us to operate in general settings, and in unfamiliar situations is our common sense. In their new book “Machines like Us:
TOWARD AI WITH COMMON SENSE” Hector Levesque and Ronald Brachman explain “why current AI systems hopelessly lack common sense, why they desperately need it, and how they can get it”. In this episode of Bridging the Gaps, I speak with Professor Ronald Brachman, one of the authors of this book. We discuss various topics covered in the book and explore the question, how we can create artificial intelligence with broad, robust common sense rather than narrow, specialised expertise.

Professor Ron Brachman is the director of the Jacobs Technion-Cornell Institute and is a professor of computer science at Cornell University. Previously, he was the Chief Scientist of Yahoo! and head of Yahoo! Labs. Prior to that, he was the Associate Head of Yahoo! Labs and Head of Worldwide Labs and Research Operations.

We start off with a detailed discussion about the progress that we have made in recent decades, in developing narrowly focused and task oriented artificial intelligence systems. Some of these systems outperform humans; however we do acknowledge and discuss the need for developing artificial intelligence systems that can operate in general settings. We discuss the concept of artificial general intelligence and explore how understanding “human common sense” and equipping AI with common sense is an extremely important milestone in our journey toward developing artificial general intelligence. We discuss the challenge of developing a clear and thorough understanding of the nature and working of human common sense. We explore how “common sense” might be modelled and incorporated in future artificial intelligence systems. We then discuss the future of artificial general intelligence.

Complement this discussion with Artificial Intelligence: A Guide for Thinking Humans” with Professor Melanie Mitchell and with Artificial Intelligence: Fascinating Opportunities and Emerging Challenges with Professor Bart Selman and then listen to 2062: The World That AI Made” with Professor Toby Walsh

By |June 4th, 2022|Artificial Intelligence, Computer Science, Future, Podcasts, Research, Technology|
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“Artificial Intelligence: A Guide for Thinking Humans” with Professor Melanie Mitchell

Recent developments in the field of Artificial Intelligence are fascinating as well as terrifying; there are extravagant promises as well as frustrating setbacks; there is great progress in narrowly focused AI applications, and there is lack of progress in the field of Artificial General Intelligence. In this episode of Bridging the Gaps I speak with professor Melanie Mitchell and we discuss the history, recent successes, huge expectations and emerging fears and frustrations in the field of Artificial Intelligence. We discuss fascinating and intriguing research that professor Melanie Mitchell discusses in her book “Artificial Intelligence: A Guide for Thinking Humans”.

Melanie Mitchell is a professor of complexity at the Santa Fe Institute in New Mexico. Her research focuses on genetic algorithms, conceptual abstraction, analogy-making and visual recognition in Artificial Intelligence Systems. Professor Mitchell originated the Santa Fe Institute’s Complexity Explorer project, an online learning resource for complex systems.

We begin our discussion by reviewing the history of this fascinating field and by discussing initial claims and hype that emerged at the start. We then discuss the transition from rule-based AI systems to machine learning approaches. We look into the successes of AI in narrowly defined task-based systems; we discuss the anomalies that emerge when the data is mildly changed. We then discuss the future development in this field and the challenges involved in making any meaningful progress towards Artificial General Intelligence and creating common sense in AI systems. The challenge of creating common sense seems similar to the challenge of finding and understanding dark matter in the field of physics, we discuss this. We look into the profound disconnect between the continuing hype and the actual achievements in AI, what the field has accomplished and how much further it has to go. We also discuss the approach of conceptual abstraction and incorporating analogy-making in AI systems. This has been a fascinating discussion about this ambitious and thought-provoking field.

Complement this discussion with “Artificial Intelligence: Fascinating Opportunities and Emerging Challenges with Professor Bart Selman and then listen to “2062: The World That AI Made” with Professor Toby Walsh

By |May 1st, 2022|Artificial Intelligence, Computer Science, Information, Podcasts, Research, Technology|
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