The AI in Business Podcast

It's more common to ask what AI can to do to win at games, but it's less common to ask what games can do to help develop AI. This is a particularly fitting topic after Google's DeepMind's defeat of Go, and in this episode we talk with New York University's Julian Togelius about his research in how games can help us develop AI. We discuss how simple AI has been used in more common video games; the 'smoke and mirrors' effect that is more often used to mimic AI; and the more innovative ways that AI are being used in gaming at present, setting precedents for the future role of AI in gaming.

What is intelligence? For some researchers, it may be quite possible to create an intelligent machine 'in a box', something without physical embodiment but with a powerful mind. Others believe general intelligence requires interaction with the outside world, inferring information from gestures and other features of functioning in an environment. Dr. Vincent Müller is of the belief that intelligence may involve more than just mental algorithms and may need to include the capacity to sense rather than just run a program. Vincent focuses on cognitive systems as an approach to AI, and in this episode he talks about what this means and implies, how this approach is different from classical AI, and what this might permit in the future if the field is developed.

You're a business, and you've collected data - now how do you now make sense of it? Bring in a technology called 'sentiment analysis', a form of machine learning that determines whether text is positive or negative. Slater Victoroff's company Indico provides a sentiment analysis API product that specializes in this task. In this episode, we talk about about the common misconceptions that businesses have about where 'big data' may be applicable, and the lessons he's learned by gaining more tangible insights from smaller sets of data for companies. He explains why big data is not necessarily better, and discusses the steps that companies should take early on to make sure they're prepared when it's time to apply machine learning to their processes.

How does automation influence society today? This is an open-ended question with likely endless answers that can be observed in many different areas of society. As a Writer, Speaker, and Professor in Media Theory and Economics, Douglas Rushkoff has made it his livelihood to examine the impacts of automation in our evolving digital society. In this episode, we speak about his 'disappointment' in how automation has been used by many industries without regard for employees' long-term well being, and how a cultural shift in industry priorities may be what's needed to make automation beneficial for the majority.

This week's in-person interview is with Dr. Adam Coates, who spent 12 years at Stanford studying artificial intelligence before accepting his current position of Director of Baidu's Silicon-Valley based artificial intelligence lab. We speak about his ideas around consumer artificial intelligence applications and impact and what he's excited about, as well as what he thinks may be more 'hype' than reality. He gives a an idea about applications that Baidu is working, to potentially influence billions of mobile and computer users worldwide. If you're interested in the developments of speech recognition and natural language processing, this is an episode you won't want to miss.

People often mark progress by what they see, but there's often much more going on behind the scenes, the up and coming, that marks actual current progress in any particular field. The same can said to be true for natural language processing, and Dr. Dan Roth's research in this field makes him privy to the advancements that most of us are bound to miss. In this episode, Dr. Dan Roth explains what the last 10 years of progress in natural language processing (NLP) have brought us, what's happening with approaches in developing this technology today, and what the next steps might be in a computer capable of real conversational speech and understanding language in context.

How do neural networks affect your life? There's the one that you walk around with in your head of course, but the one in your pocket is an almost constant presence as well. In this episode, we speak with Dr. Yoshua Bengii about how the neural nets in computer software have become more ubiquitous and powerful, with deep learning algorithms and neural nets permeating research and commercial applications over the past decade. He also discusses likely future opportunities for deep learning in areas like natural language processing and individualized medicine. Bengio was a researcher at Bell Labs with Yann LeCun and Geoffrey Hinton, now at Facebook and Google respectively, and was working on neural nets before they were the "cool" new AI technology that they're seen as today.

Statements about AI and risk, like those given by Elon Musk and Bill Gates, aren't new, but they still resound with serious potential threats to the entirety of the human race. Some AI researchers have since come forward to challenge the substantive reality of these claims. In this episode, I interview a self-proclaimed "old timer" in the field of AI who tells us we might be too preemptive about our concerns of AI that will threaten our existence; instead, he suggests that our attention might be better honed in thinking about how humans and AI can work together in the present and near future.

TechEmergence has had a number of past guests who have talked about neural networks and machine learning, but Dr. Pieter Mosterman speaks in-depth about the pendulum swing in this approach to AI from the 1960s to today. What we call neural networks as a general approach to developing AI has come in and out of favor two or three times in the last 50+ years. In this episode, Dr. Pieter Mosterman speaks about the shift in this approach and why neural networks have gone in and out of favor, as well as where the pendulum may take us in the not-too-distant future.

Few astrophysicists are as decorated as Martin Rees, Baron Rees of Ludlow, who was a primary contributor to the big-bang theory and named to the honorary position of UK's astronomer royal in 1995. His work has explored the intersections of science and philosophy, as well as human beings' contextual place in the universe. In his book "Our Final Century", published in 2003, Rees warned about the dangers of uncontrolled scientific advance, and argued that human beings have a 50 percent chance of surviving past the year 2100 as a direct result. In this episode, I asked him why he considers AI to be among one of the foremost existential risks that society should consider, as well as his thoughts around how we might best regulate AI and other emerging technologies in the nearer term.

When we think about AI, we often think about optimizing some particular task. In most circumstances through computation there is an optimal chess move, or an optimal way to determine pattern in data, or solve a math problem, or route info through servers. Most of us are aware of these uses, but what about creative tasks? Can these also be optimized? If we want to give a computer information and tell it to create powerpoint slides, is there an optimal way to create such slides? Dr. Philippe Pasquier's computational research is focused on artificial creativity. In this episode, we talk about how to define a very new field, train machines in this area, and also discuss trends and developments that might permit such technology to thrive in the next 10 years.

There's a small lab in Pennsylvania that may know your gender, age, and understands facets about your personality, whether you're introverted or extroverted, for example…and it's using machine learning to help make conclusions from social media information. For those who are raising an eyebrow, know that they're not tapping into people's accounts without permission. The described study is happening at University of Pennsylvania and is led in part by Dr. Lyle Ungar. In this episode, we talk about the focus of his work - on finding patterns between users and their language on social media content, and building an understanding for how this information might help individuals and communities in the future.

We've featured a number of artificial intelligence researchers on the show, but today we switch gears and dive into the business side of the industry. In this episode, Dr. Mazin Gilbert (who earned his PhD in Engineering) breaks down AT&T's efforts to make more intelligent systems large-scale. How do they train their network to route traffic through the right nodes on holidays, when certain areas of traffic are overloaded? How can a system know, based on signals from hardware, which pieces might be going bad and need replacing and send out a message to alert the company? Making a network 'aware' is a large challenge, but Mazin gives an insider's perspective as to how economic and business pressures are driving AT&T to implement machine learning technologies in order to remain profitable.

Are we losing something with technology? There are two sides to every argument, including this one. Dr. Sherry Turkle is of the belief that there's enough mounting scientific evidence that points toward loss of empathy and self knowledge due to increasing interaction with machines. In this episode, we discuss Dr. Turkle's research and her subtle fears for the future, particularly of those about machines that replicate emotions or conversation but that don't actually feel anything - is the ability to form real connections between two beings at risk of being lost?

A lot of AI applications are not really "smart", at least not in the sense of the word as most humans might envision a true artificial intelligence. If you know how Deep Blue beat Gary Kasparov, for example, then you may not believe that Watson is a legitimate thinking machine. Our guest this week, Dr. Pei Wang, is of the belief that building a Artificial "General" Intelligence (AGI), what researchers define as an entity with human-like cognition, is a separate question from figuring out AI applications in the more narrow sense. In this episode, Dr. Wang lays out three differentiating factors that separate AGI from AI in general, and also talks about three varied and active approaches being taken to try and accomplish AGI.

It goes without saying that the brain is difficult to understand, with the billions of neurons, fine individual synapses between each neuron, and the different regions responsible for the innumerable behaviors exhibited by human beings. A new burgeoning and promising intermediary field called Connectomics is making waves in mapping the brain and figuring out how these various connections work together to make us sentient. In this episode with Dr. Olaf Sporns, who is in part credited with coming up with the term Connectomics, we explore the progress that's been made in this new field in the past decade, and take a tentative but hopeful look ahead at what the next decade might bring as the field progresses into its adolescence.

Ever had the perfect book recommended to you by Amazon or gave a pleasantly-surprised thumbs up for a song selected for you by Pandora? Both services are powered by recommendation engines, which are gaining steam int he commercial space. In this episode, we speak with Entrepreneur Raefer Gabriel, who works for Delvv on the commercial applications of recommendation engines. We talk about how this technology works, and how it comes to learn from reviews, ratings, and consumer interactions. Gabriel also gives perspective on how these engines might be enhanced and applied in the future, a good topic for those of you in the startup world.

The beauty of a platform like eBay is that you can set a price that you're willing to spend and let eBay do the bidding long after you've left the site. What if, in similar fashion, your washing machine could turn on and serve up clean clothes once it had found the cheapest rate and time of day by autonomously communicating with local electricity providers? In this episode, we discuss multi-agent intelligent systems with Computer Scientists Dr. Mehdi Dastani, who provides a perspective on how this emerging dynamic technology is changing the landscape of how and how companies and governments operate, allowing for greater systemic change that might not be possible otherwise.

Over the last decade, many first-world militaries have developed, and in some cases deployed, autonomous "killer" robots. Some proponents believe that such robots will save human lives, but another side believes that an accidental arms race of this type would yield long-term detriments that outweigh any good. University of Sheffield's Dr. Noel Sharkey stands by the latter argument. As Co-Founder for the International Committee for Robot Arms Control, he has spent a good part of the last decade trying to create an international ban on such robots. In this episode, he speaks about the developments in the domain of autonomous killer robots, as well as how groups of global leaders might come together to convince nations and other global policy platforms to adhere to such an agreement for the benefit of all humankind.

Most of us forget that just about a decade ago, Facebook's software was incapable of tagging people in a photo, but today can so without difficulty, sometimes without us even knowing. Machine vision has progressed to the point where it's also common for computers to be able to pick out dogs from cats in images, another task that was not possible 10 years ago. In this episode, we talk with Dr. Irfan Essa, an expert in Computer Vision at the Georgia Institute of Technology (GA Tech), about progress made in machine vision over the last 10 years, related projects in the works today, and where machine vision may be headed in the next decade.

Have you ever seen a humanoid robot and felt creeped out? In this episode, we talk with Robotics Engineer Derek Scherer about the psychology of the uncanny valley and our relationships with robots. Scherer talks about the factors in robotics that tend to spook people and provoke a feeling of disgust, and how we might be able to move beyond this resistance as they become a more active part of the social fabric of our society.

Most of society functions based on a general social contract i.e. we work to contribute to society and earn income to acquire goods. Those who can't earn an income are required in some fashion to validate why. In this episode with Federico Pistono, an entrepreneur, author, and futurist, asks if this contract is the only way to exist as a society. In a more automated world, is this contract the best long-term structure for the common welfare? Pistono and I discuss what a future society might be like with an altered social contract i.e. a general minimum wage for all, how this might affect our approach to "work", and the avenues for testing out such a contract in society today. .

Neural network - it's almost a buzz word, but it was looked down on during certain periods of AI development. Nonetheless, most of the public is not aware of what a neural network is, how it works, and how we can create an artificial one. CEO and Founder of Imagination Engines, Inc., Dr. Stephen Thaler gives us some insight today on how neural networks create what we call creativity, and provides his perspective on how a neural net eventually merges to give way to consciousness.

Cyber security is closely linked to advances in artificial intelligence. In this episode, we speak with Dr. Roman V. Yampolskiy about the cyber security factors and risks associated with AI. How is AI both causing risks, and how can AI be used to combat those risks? We dive briefly into the future to speak about some of the potential 'super' AI risks to cyber security and touch on what can be done now to help hedge the unknown.

It's common knowledge that scientists study the brain to understand how to replicate intelligence in machines; it's less commonly known that scientists also use machine models to understand how the mind works. In this episode, we talk with Dr. Ashok Goel, a researcher in the field of cognitive systems who sheds light on this idea. Dr. Goel also speaks about his perspective on where machines are becoming more creative, and what the future might look like if machines begin to reflect on their "identities" as humans do.

Over 100,00 years ago, it may have been advantageous for human beings to be hyper aware of other living things for the purposes of survival. In the future, between the IoT and advances in AI, we once again find ourselves ever more aware. Erik Davis, the author of TechGnosis and a praised journalist and speaker, explores the intersection of the technical, spiritual, and often mystical. In this episode, we discuss how our gut reactions to AI often spring from evolutionary or cultural reasons, and how this shapes our reactions to technology and guides our development of it in the 21st century.

Most of us can admire AI such as Siri, Watson, and other agents shaping the fabric of future AI-powered entities, but it's also possible to admire them as a "dead end". Dr. Alexei V. Samsonovich is one researcher who believes that we won't be close to perceiving AI as 'conscious' machines until we can grant them the necessary emotional intelligence. Though a lot of progress has been made in field of intelligent agents in the last 10 years, many researchers who are in the same camp as Samsonovich are now on a mission to develop human-like intelligence, cognitive abilities, emotional and social intelligence, and common sense reasoning.

Dr. James D. Miller, an Economics and AI researcher who received his doctorate from the University of Chicago, sheds light on how economics factors into our increasingly automated world, where development is growing exponentially. We discuss how this acceleration may (or may not) help materialize the "Singularity", the theorized point at which society is so drastically revolutionized by technologies that we never return to our past ways of life.

Dr. Danko Nikolic, a scientist at the Max-Planck Institute for Brain Research, asks and works to answer questions about how our physical neuronal connections create the mind's perceptions. In the realm of AI, Danko zones in on learning in a newborn human and compares that to a robot. He asks how we can take human lessons, what's built into our genome, and apply that to construct a more generally intelligent AI, in a way that is not being done today.

After receiving her PhD in Computer Science from the University of New York in 2002, Dr. Sheryl Brahnam's research interests steered her toward studying human abuse and misuse with computers, specifically conversational agents such as Siri, phone-based auto agent systems, and even chat support. Her research yields questions in relative new territory: Are AI prone to receiving misuse?; why do people misuse these agents in ways that they would not treat a human?; and, what types of regulations will we need as AI improves and becomes more intelligent?

Dr. Joscha Bach is a software developer and researcher, who is currently developing a cognitive AI framework at MIT Media Lab and the Harvard Program for Evolutionary Dynamics. In this episode, he speaks about the troubles in projecting when strong AI may be developed, and sheds light on the trends taking us there, including deep and reinforcement learning.

Is it possible to make AI friendly to humans via software or will we have to hardwire consideration for humanity into an advanced AI? Louis Del Monte, best-selling author and expert in the field of Artificial Intelligence, argues the latter. In this discussion, Del Monte talks about how he came to these conclusions and wrote a book on the topic, in part inspired by a particular AI study that provoked his grave concern for where AI may take us in the future.

Dr. András Kornai wants to put emphasis on the real and near-term ethical considerations around AI. In this interview, Kornai peels off the Hollywood myth "layers" around consciousness and AI in order to spotlight the very real, present, and advancing algorithms. He explains how such algorithms, which are slowly taking over the financial, medical, and automotive industries, are increasingly relevant as machines start to govern and make more decisions in our everyday interactions.

Daniel Berleant is an expert in information science and artificial intelligence, and is the author of the book he Human Race to the Future: What Could Happen - and What to Do. In this interview, we discuss how robots and automation are already affecting industry, and how these impacts might shape not only the future landscape of our economy, but also our conception of what it means to work and earn a living.

Katherine Hayles is best known for her work as a postmodern social and literary critic. Now a professor at Duke University, Hayles joins TechEmergence for a discussion about the difference between consciousness and cognition, from the features that differentiate the two to the types of technologies that facilitate each. Hayles contributes her views on how the technologies of the future may impact human consciousness and the very role of human being

Could we one day upload ourselves into a computer or chip? Keith Wiley thinks that one day, we might be able to replicate consciousness within another entity. In this episode, Dr. Wiley speaks to us about why uploading human identity in a computer substrate might be possible in the coming decades, and the type of progress we're making today in the areas of computing and mapping the brain.

When should we care about robots? How quickly should and will that change? These are just some of the thought points addressed by Professor David Gunkel, whose work on the moral valuations of AI is some of the first of its kind. In this interview, we consider the extent to which our "moral weighing" of other entities is arbitrary, and ask what a biased process might imply when we create other aware entities.

We talk a lot about the future of technology on TechEmergence - the long-road potentials and ethical considerations that intersect the various paths of artificial intelligence. But keeping the conversation real and present necessitates looking through binoculars rather than a telescope from time to time. In this episode, Eyal Amir, Associate Professor of Computer Science at University of Illinois and Co-Founder of Parknav and AI Incube, Inc., gives his zoomed-in perspective of the types of technological progress that he believes will be relevant in the next 5 to 10 years.

Do you need a body to think? This is a worthwhile (and also a perplexing) question, and an ongoing debate amongst roboticists. Cognitive Roboticist Dr. Mark Bickhard is part of a field of belief that cognition and intelligence - and maybe consciousness itself - requires embodiment and direct interaction with the world. In this interview, he discusses the concept of normative function and self maintenance in entities, and why this matters when it comes to thinking.

Stephan Vladimir Bugaj is a modern visionary with extensive experience in screenwriting, technical artistry and directing in animation and games. He is the Creative Director at Hanson Robotics, where he specializes in robot personality and functional design. He is also a writer-director for WakingUp media and Visioneer studios, two screenwriting and production companies, and part of the story "brain trust" for Limitless VR. Stephan worked for over 10 years as a screenwriter and technical director with Pixar Animation Studios, and before that was a multimedia researcher at Bell Labs and artificial intelligence developer at Intelligenesis/Webmind. In this episode, Stephan draws on his robotics background to articulate what it takes to give a humanoid robot a "personality", and explains the differences between responses and propensities. Androids are already making news in the entertainment and retail industries, but we delve into why the health sector is next, and how culture might influence social acceptance.

Do lobsters really have something to teach us about developing AI and robotics? Dr. Joseph Ayers, a professor of Marine and Environmental Sciences at Northeastern University, has dedicated his research and work to the subject and has paved new directions for the future of AI and robotics in the domain of biomimetics. In this episode, Dr. Ayers provides a comprehensive overview of his development of autonomous underwater robots that help discover and destroy dangerous underwater land mines, and the potential for other animal-like robots to perform other "dull and dangerous" services for humankind. He provides a concluding perspective on two major obstacles facing robotics, one of which is the concept of autonomy, providing valuable insight in light of the current events around autonomous AI.

Dr. Bruce MacLennan is an Associate Professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee Knoxville (UTK), as well as past editor-in-chief of the International Journal of Nanotechnology and Molecular Computation. His research in natural computation has led to active, interdisciplinary involvement in the fields of neuroscience, cognitive science, and philosophy. In this episode, Bruce discusses how studying the mind has influenced, and will continue to influence, the development of artificial intelligence. In a largely digital world, he turns a clarifying light on the topic of digital versus analog computing, and articulates on how the latter may be making a slow comeback in the wake of discoveries in neural information processing.

Dr. Peter Boltuc has a PhD in Philosophy and is currently a Professor at University of Illinois Springfield. His background in Moral and Political Philosophy has leveraged his research into the subjectivity of moral experience and the moral implications of machine consciousness. In this episode, Peter discusses whether machines could ever be granted consciousness. He believes, hypothetically, that we could create such machines, and elaborates from an ethical perspective on why we may want to "curve moral space" in a way that values human-level sentience and moves us toward living harmoniously with such machines.

Dr. Gary Marcus is the Director of the NYU Center for Language and Music, and Professor of Psychology at New York University, and is author of well known books such as The Birth of the Mind, The Algebraic Mind: Integrating Connectionism and Cognitive Science, and the New York Times Editor's Choice called Kluge: The Haphazard Construction of the Human Mind. In this episode, Dr. Marcus gives us some insight as to what the brain is good and bad at, and why - in addition to what this might imply for the future of human enhancement.

Dr. Joanne Pransky received her doctorate from Tufts University in the mid 1980's, and began championing public awareness and exposure to robotics and AI technology, playfully calling herself the "first robot psychiatrist." Since then, she's been featured on CNN, The Discovery Channel, the Sci-Fi Channel, and even the Tonight Show with Jay Leno - aiming to expose the world to technology and it's ethical implications. In this interview, Dr. Joanne speaks with me about the virtues and vices of how the media portrays AI to the public… and why she likes recent AI movies like "Her" and "Ex Machina," but questions scandalous newspaper headlines about industrial robots "killing people", as well as her thoughts about the types of conversations that she believes America (and world) should be having in order to move technology forward safely and fruitfully.

Dr. Hables Gray graduated with a PhD in applied philosophy from UCAL Santa Cruz, and is best known for his writings on technology, war, and cyborgs (the combination of organic and inorganic, the evolved and the invented). In this interview, Dr. Hables Gray explains his ideas around how seemingly mundane technologies and social media help to blur the line between man and machine, as well as his predictions for how car cyborgs will progress in the coming decades (including the integration of drone technology, brain-machine interface, and more).

Sean Blacknell has spent the last year working on a filmed called "The Future of Work and Death," based on interviews with futurists, economists, philosophers, and other experts - with an aim to bring the film to Sundance and other prominent festivals in the coming year. In this interview, Sean explains some of the most meaningful lessons he's gained about the future of humanity from all of the interviews for his own film.

Dr. Roger Schank received his PhD from Stanford, taught at Yale, and altogether has spent around three decades attempting to solve the big problems of artificial intelligence. In this interview, Dr. Schank talks about a kind of helpful "teaching" artificial intelligence that would go beyond Siri and help us to make the right decisions at the right times given our own objectives. He explains why he believes such a project is not on Google's agenda, and what he believes might be required to create such an AI.

Dr. Nick Montfort doesn't hold Shakespeare and DaVinci as the high water mark of "creativity," nor does he believe that human creative endeavor is the only worthwhile kind. In this interview, Dr. Montfort shares some of his own examples of how computers can aide the creative process in ways that might result in "art" that humans aren't capable of making alone. In addition, he provides his insight as to where the intersections of artificial intelligence and "creativity" might really lie.

Dr. Jonathan Moreno's book "Mind Wars" has contributed to his current reputation as one of the most prominent bioethicists in America today. In this interview, Dr. Moreno shares his thoughts about the government agencies like DARPA and the NIH are invested in and involved with the latest biotechnology initiatives, from neuro-prosthetics to psychedelics and beyond. He also shares with us his ideas about how civilian needs are often a prime driver of the direction of biotechnology development (even for behemoths like DARPA).