Azeem Azhar's Exponential View

For Jürgen Schmidhuber, a recognized pioneer in AI, artificial intelligence is much more than another technological revolution. He sees it as the opportunity to transcend humanity and biology. In this conversation, Jürgen and Azeem Azhar discuss what the next thirty years of AI will look like. Jürgen and Azeem also discuss: The role of Long Short-Term Memory architecture in recent AI breakthroughs. Why the next AI wave will see machines actively shaping the data that they perceive. The second- and third-order consequences of bringing these more sophisticated artificial neural networks into our world. Further reading: “An AI taught itself to play a video game – for the first time, it’s beating humans” (The Conversation, May 2019) “Moving Beyond Cloud Computing to Edge Computing” (CableLabs, May 2019) “An All-Neural On-Device Speech Recognizer” (Google, March 2019) “Google’s head of translation on fighting bias in language and why AI loves religious texts” (The Verge, January 2019) Jürgen Schmidhuber Azeem Azhar @azeem www.exponentialview.co

One of the founders of complexity economics, W. Brian Arthur, joins Azeem Azhar to discuss how artificial intelligence is ushering us into the age of the autonomous economy with radical implications for our society. In this podcast, Brian and Azeem also discuss: Why the decision-making ability of AI will have a different class of impact on the economy than previous ‘landmark’ technologies like the printing press. Whether it is possible to have publicly available decision-making enabled by artificial intelligence outside the proprietary enclaves of Silicon Valley monopolies. Increasing Returns Theory and how to generate good governance in a digital economy with dominant market actors. Further reading: “A Short History Of The Most Important Economic Theory In Tech” (Fast Company, December 2016) “Where is technology taking the economy?” (McKinsey Quarterly, October 2017) “The second economy” (McKinsey Quarterly, October 2011) “Increasing Returns and the New World of Business” (HBR, July-August 1996) W. Brian Arthur Azeem Azhar @azeem www.exponentialview.co

Artificial intelligence is unlocking new value in the banking and finance industry, but incumbents are struggling to keep pace. Azeem Azhar discusses what this means for the industry and its customers with Citi Research’s Global Sector Head for Banks Ronit Ghose, and the founder-CEOs of two leading innovators: Daniel Schreiber of Lemonade Insurance and Rishi Khosla of OakNorth Bank. Paul and Azeem also discuss: The huge role technology debt plays in obstructing legacy banks from innovating. How social networks, the smartphone, and AI grew exponentially and converged to mount a challenge to the traditional banking industry. The ways AI is cutting friction on the customer side. The ability to identify the sources of client or third-party data that can generate an algorithmically-powered image of the client and provide an insight into their ‘real’ level of risk. Further reading: “Digital Disruption: How FinTech is Forcing Banking to a Tipping Point” (Citi Velocity, March 2016) “Bank X: The New New Banks” (Citi Velocity, March 2019) “The Future Of Banking: Fintech Or Techfin?” (Forbes, Aug. 27, 2018) “Bank 4.0 Will Be All-Digital, Low-Overhead, Mobile-First” (Forbes, April 19, 2019) Ronit Ghose @ronit_ghose Daniel Schreiber @daschreiber Rishi Khosla @rishi_khosla Azeem Azhar @azeem www.exponentialview.co

AI is the fastest-growing industry that Accenture’s CTIO Paul Daugherty has ever experienced. He joins Azeem Azhar to discuss how AI can help businesses across a broad range of industries enhance the value they offer customers. Paul’s 2018 bestselling book Human + Machine: Reimagining Work in the Age of AI laid the foundations for companies that want to harness AI to help innovate and grow quickly. Paul and Azeem also discuss: AI as a general-purpose technology and how to set priorities for its application. How critical it is to have data at the heart of your business. Can you use AI effectively if you don’t utilize the “data network effect?” The difference in an AI system that can interact with and modify human behavior from a company that puts out services or products that are highly addictive. How the rush to individualization moves us into “The Trust Age.” What are the practical steps companies can take to (re)build consumer trust? Self-regulation vs. external regulation, and the challenges of appropriately balancing regulation and innovation. Further reading: “The Future of AI Will Be About Less Data, Not More” (HBR, Jan. 14, 2019) “Accenture Interactive Launches Groundbreaking Artificial Intelligence Solution to Tackle Elderly Loneliness” (Accenture, April 30, 2019) “Using AI to Make Knowledge Workers More Effective” (HBR, April 19, 2019) “Hey Google, sorry you lost your ethics council, so we made one for you” (MIT Technology Review, April 6, 2019) “From Principles to Action: How do we Implement Tech Ethics?” (Industry Ethicists, April 17, 2019) Paul Daugherty @pauldaugh Azeem Azhar @azeem www.exponentialview.co

Director of the Humans and Autonomy Lab at Duke University and one of the first female fighter pilots, professor Missy Cummings debates the current state of autonomy with Azeem Azhar. Taking a stance of techno-realism, Missy explains why we’re not even close to developing Level 5 autonomy in driving and why robotic surgery is still not safe. In this podcast, Missy and Azeem also discuss: The nonlinear upward movement across levels of automation. While early developments may take similar amounts of time and money, the final advancements demand exponentially more. The psychology behind why we will almost certainly always have human pilots on commercial flights. Why the United States’ certification system, based on equivalence, has never been suitable for autonomous systems — and how training regulators and policymakers alongside engineers might spark regulatory improvements that would foster safe innovation. Parallels between the cultures of Silicon Valley and the U.S. military and thoughts on why gender equality still hasn’t been achieved. Further reading: “Technological, Regulatory Innovation Needed to Ensure Safety in Autonomous Vehicle Research” (Duke, April 9, 2018) “FDA clears new robotically-assisted surgical device for adult patients” (U.S. Food & Drug Administration, Oct. 13, 2017) “Robotic Surgery: An Example of When Newer Is Not Always Better but Clearly More Expensive” (The Milbank Quarterly, March 2016) “‘I Don’t Know How Professors Teach Without Fighter-Pilot Experience'” (The Atlantic, April 26, 2018) “Ex-pilot: I understand Martha McSally’s pain” (CNN, March 8, 2019) Missy Cummings @missy_cummings Azeem Azhar @azeem www.exponentialview.co

Michigan State University senior vice president Stephen Hsu, a theoretical physicist and the founder of Genomic Prediction, demonstrates how the machine learning revolution, combined with the dramatic fall in the cost of human genome sequencing, is driving a transformation in our relationship with our genes. Stephen and Azeem Azhar explore how the technology works, what predictions can and cannot yet be made (and why), and the ethical challenges created by this technology. In this podcast, Azeem and Stephen also discuss: FDA approval of the first genetic treatment for monogenic conditions and the work towards developing treatments for polygenic conditions like diabetes and cancer. How this technology might exacerbate existing social inequalities or create new ones; is it just an issue of access, or does it go further? Developing best practice protocols for governance and regulation of genomic technologies. Further reading: “FDA approves novel gene therapy to treat patients with a rare form of inherited vision loss” (Dec. 19, 2017) “Genomic Prediction of Complex Disease Risk” (Dec. 27, 2018) “How Direct-to-Consumer Genetic Testing Services Led to the Capture of the Golden State Killer” (September 2018) Stephen Hsu @hsu_steve Azeem Azhar @azeem www.exponentialview.co

With healthcare under extreme commercial and political pressure, the doctor-patient relationship is at a low point — and risks further deterioration. But digital technologies promise to revolutionize the daily delivery of care. Renowned digital medicine pioneer Dr. Eric Topol and Azeem Azhar discuss what this could mean for medical professionals, patients, and national healthcare systems. In this podcast, Eric and Azeem also discuss: Issues of access: equality of access and coping with differential patient capability when participating in digital therapeutics. The impact of GDPR on the need for ‘explainable AI’ in medicine. Algorithmic surveillance and whether the traditional management culture of ‘patching’ bugs translates to digital therapeutics and pharmaceuticals. Data security and the possibility of a data ‘bill of rights’ for patients and consumers of medical tech. Further reading: “The Topol Review” (February 2019) “Mobile health devices diagnose hidden heart condition in at-risk populations” (July 10, 2018) “A call for deep-learning healthcare” in Nature Medicine Vol. 25 (Jan. 7, 2019) “NVIDIA, Scripps Research Translational Institute Partner on AI for Genomics, Digital Health Sensors” (Oct. 23, 2018) Dr. Eric Topol @EricTopol Azeem Azhar @azeem www.exponentialview.co

“We haven’t really understood the power of the state,” argues economist Mariana Mazzucato, warning that this has impacted the rising inequality in wealth creation and distribution. Mariana and Azeem Azhar discuss the role of government in innovation and business growth, risk-taking as the new mentality of bureaucracy, and how the benefits of entrepreneurial innovation have been misread. Above all, the case is made for a new theory of value in today’s economy. In this conversation, Mariana and Azeem also discuss: The role of the entrepreneurial state: moving away from the concept of the state as a facilitator and towards the state as an actor in the future of public-serving innovation. Why the GDP model is flawed — but why we should retain it as one of several economic indicators. Creeping privatization of the ‘data economy.’ Further Reading: “Yes, Government Creates Wealth” (September 2018) “Let’s make private data into a public good” (June 27, 2018) “Rethinking the Smart City” (January 2018) “The unlikely tech giant empowering citizens through data” (March 12, 2019) “Strategic design for public purpose” (March 8, 2019) Mariana Mazzucato @MazzucatoM Azeem Azhar @azeem www.exponentialview.co

Our society has become increasingly reliant on data, but its value is not accessible to all. Of the 16 billion terabytes of data created globally in 2016, only 1% was analyzed. Among other discrepancies, the growing data monopolies concentrate power over certain technologies such as artificial intelligence precluding their positive impact on society. Trent McConaghy, AI researcher and the founder of the decentralized data exchange, Ocean Protocol, is aiming to solve this by enabling individuals and organizations to share, monetize, and access data. In this conversation, Trent and Azeem Azhar discuss: The real-world impact of deep learning and error reduction, and why we have not yet fully leveraged data’s learning potential. Early use cases of successful data exchange in mining and autonomous driving. Drawing distinctions between human rights and tradable property, should ownership of personal data be protected as a human right? Further Reading: “The Unreasonable Effectiveness of Data” (2009) “The Web3 Data Economy Towards a Transparent, Permissionless Ecosystem to Spread the Benefits of AI” (Nov. 22, 2018) “Major Automakers, Startups, Technology Companies and Others Launch Mobility Open Blockchain Initiative (MOBI)” (May 4, 2018) “Is It Your Data” (Jan. 22, 2019) “Should we treat data as labor? Let’s open up the discussion” (Feb. 21, 2018) “We need to own our data as a human right — and be compensated for it” (Jan. 21, 2019) “This AI Company Is The Future Of Gold Exploration” (February, 2019) Open Data Impact Map Trent McConaghy @trentmc0 Azeem Azhar @azeem www.exponentialview.co

“Intelligence is central to everything humans do, and artificial intelligence should be no exception.” With these words, Joanna Bryson urges for stronger professional standards for software engineers and experts designing intelligent-like systems. Joanna is a tenured associate professor at the University of Bath in the United Kingdom, where she founded the Bath Intelligence Systems group. She is one of the world’s leading AI researchers, uniting the perspectives of computer science, psychology, and biology in her work. In this podcast, Azeem Azhar and Joanna explore: The role of goals in conceptualizing and programming intelligence systems — and who sets these goals? The risks and inadequacies of anthropomorphizing AI. The critical importance of assuring ongoing human involvement in AI systems. The explainability of AI systems and litigation over the definition of ‘explanation’ in light of EU’s General Data Protection Regulation (GDPR). Further Reading: Group Agency: The Possibility, Design and Agency of Corporate Agents (April 7, 2011) UKRI Centre for Doctoral Training in Accountable, Responsible and Transparent AI (ART-AI) Joanna Bryson et al, “Semantics derived automatically from language corpora contain human-like biases” (April 14, 2017) Nick Bostrom, “Ethical Issues in Advanced Artificial Intelligence” Joanna Bryson, “No one should trust AI – AND – Presenting robots as people stops us thinking clearly about AI” (Dec. 23, 2018) Joanna Bryson @j2bryson Azeem Azhar @azeem www.exponentialview.co