New York-based insurance provider Travelers, with 30,000 employees and 2021 revenues of about $35 billion, is in the business of risk. Managing all of its facets, of course, requires many different approaches and tools to achieve beneficial outcomes, and Mano Mannoochahr, the company†s SVP and chief data & analytics officer, has a crow†s nest perspective of immediate and long-term tasks to equally strengthen the company culture and customer needs. We needed to think about those disciplines together and make progress to maximize the benefit to our customers and our business overall.†Another focus is on finding and nurturing talent. It†s a pressing issue not unique to Travelers, but Mannoochahr sees that in order to deliver on those disciplines advancing analytics to foster a healthier business, he and his team recognize the need to cast a wider net. This is kind of a team sport for us, so it†s not just data scientists but software engineers, data engineers, and even behavioral scientists to understand how we empathize and best leverage the experience that our frontline employees have, as well as position these capabilities in the best way so we can gain their trust and they can start to trust the data and the tool to make informed decisions.

Creating artificial intelligent agents that are high-fidelity simulations of natural agents will require the engagement of behavioral scientists. However, agent programming systems that are accessible to behavioral scientists are too limited to create rich agents, and systems for creating rich agents are accessible mainly to computer scientists, not behavioral scientists. We are solving this problem by engaging behavioral scientists in the design of a programming language, and integrating reinforcement learning into the programming language. This strategy will help our language achieve adaptivity, modularity, and, most importantly, accessibility to behavioral scientists. In addition to allowing behavioral scientist to write rich agent programs, our language -- AFABL (A Friendly Behavior Language) -- will enable a true discipline of modular agent software engineering with broad implications for games, interactive storytelling, and social simulations.

LONDON – Helicopter cash, climate crises, smart cities and the space economy -- investors have all those possibilities ahead as they enter the third decade of the 21st century. They go into the new decade with a spring in their step after watching world stocks add over $25 trillion in value in the past 10 years and a bond rally put $13 trillion worth of bond yields below zero. They also saw internet-based firms transform the way humans work, shop and relax. Now investors are positioning for the tech revolution's next 10 years. Could we see a repeat of the Roaring '20, as the 1920s were known -- years of prosperity, technological innovation and such social developments as women winning the right to vote?

Recognition of the powerful pattern matching ability of humans is growing. As a result, humans are increasingly being deployed to make decisions that affect the well-being of other humans. We are starting to see the use of human decision makers in courts, in university admissions offices, in loan application departments, and in recruitment. Soon humans will be the primary gateway to many core services. The use of humans undoubtedly comes with benefits relative to the data-derived algorithms that we have used in the past.

Deep Blue's 1997 victory over world champion Garry Kasparov was the beginning of the end of mankind's chess dominance. A game once believed to be the pinnacle of human intelligence was being taken over by computers. In 2005--a mere eight years later--the world's seventh ranked player was thrashed by a supercomputer, managing only a draw over six games. And in 2006, world champion Vladimir Kramnik was defeated by Deep Fritz, a software program running not on a supercomputer, but a model you could purchase at your neighborhood electronics store. Today, the state of play is decidedly one-sided.

At the recent Forbes CIO Summit in Half Moon Bay, California, I had the opportunity to share the stage with about a dozen leading technology leaders from a variety of different companies. Included among them were CEOs, CIOs, and venture capitalists. After the event concluded, I reached out to a number of contacts of mine who were in the audience to gauge what they found most interesting, and the person who was mentioned more than any other was Kyle Nel, who is the Executive Director of Lowe's Innovation Labs at Lowe's Home Improvement. You might think to yourself, "'Innovation Labs' sounds interesting, but Lowe's? How innovative can that be?" Very innovative, as it turns out.