Harish Batlapenumarthy always believed culture is more important than anything else at work. He and the team at Emtropy Labs set out to identify how groups communicate in companies using machine learning. They ultimately landed on listening to customer feedback to automatically generate insights into customer experience metrics like churn risk. Listen and learn...A better way to identify customer sentiment using supervised machine learningWhat techniques are most effective for labeling training dataWhy traditional methods of measuring customer satisfaction are poor at understanding actual customer satisfactionHow to mitigate the impact of bias in training dataHow Harish defines "responsible AI"Why there will always be a need for human customer success managersReferences in this episode...Emtropy LabsChandra Khatri from Got It AI on AI and the Future of Work

Eric Daimler advised the Obama administration on how to have conversations about AI. His work led to the creation of the AI office within the Science Advisory Group of The White House which has now become a cabinet-level position reporting to The President. Eric's a walking encyclopedia about AI policy and he shares all in this fascinating discussion about the future of technology, ethics, and society.Listen and learn...What it's like to shift from academia to venture capital to entrepreneurship to public serviceHow the growth of data sources as well as data creates an unimaginably large number of data relationshipsHow Conexus applied categorical algebra to bring together 300k databases at UberWhy it's data integration limitations that are constraining AI innovation more than compute, storage, or algorithms How category theory is required for smart contracts on blockchains and quantum computing How Eric thinks about when AI should make autonomous decisions vs. requiring human intervention The role of regulation in managing job elimination due to AI The ethical framework Eric proposes for evaluating what decisions AI can and should makeThe challenges of enforcing data policies like GDPR in the EUHow Eric defines "responsible AI"References in this episode...Eric's company, ConexusThe President's Council of Advisors on Science and TechnologyAftershock which includes a chapter by EricEric on Twitter

Mahesh Ram, founder and CEO of Solvvy, set out to "give everyone back time". His company was recently acquired by Zoom to improve customer experiences using conversational AI. Mahesh was inspired by his work using speech recognition to improve business English learning at Global English. Solvvy was founded in 2015 and has raised funding from an exceptional group of investors including previous "AI and the Future of Work" guest Rory O'Driscoll from Scale Venture Partners. Listen and learn...About the three waves of chatbot technologyWhy "more deflection" doesn't need to translate into "lower satisfaction"How Calm uses Solvvy to deliver automated customer serviceWhy AI based on semantic similarity is better than traditional scripted chatbotsWhy "putting the user first" and "not hiding the live agent" is essential for gaining consumer trust in chatbotsHow to address latent bias in data used to train AI modelsWhy bots will never replace live agentsReferences in this episode...Rory O'Driscoll from Scale Venture Partners on AI and the Future of WorkSolvvy acquired by ZoomChandra Khatri from Got It AI on AI and the Future of Work 

Chandra Khatri,  Chief Scientist and Head of AI at Got It AI, was a key team member in the early days of AI at eBay, Amazon, and Uber. He has been on the cutting edge of NLP research for more than a decade and now leads AI at Got It AI. Chandra and the team are making it easier for customers to have conversations with bots.  He's making innovative use of transformers and active learning to use "small data" to train sophisticated large language models to automatically answer customer questions in fields as diverse as healthcare, financial services, education, and defense.Listen and learn… What the AI culture is like at eBay, Amazon, and Uber About transformers, why they’re important, and how they're improving NLP accuracy How we’ve moved AI from search ranking (recommender systems) to other use cases including operations and bots How the rise of open source and no-code tools is making “Google-like” AI maturity accessible to every company How startups with limited access to data can use transfer learning to improve AI accuracy What’s holding back broader adoption of AI in the enterprise How the rise of Technical Product Managers (TPMs) is bridging the gap between engineers and business analysts How to eliminate bias from training data How long before we’ll all have a personal JARVIS References in this episode… Got It AI Chandra on LinkedIn Hugging FaceChristopher Nguyen on AI and the Future of Work

Paul Lee, serial entrepreneur and co-founder of Synesis One, combined his love of games with a passion for NLP and AI. He realized language ontologies can be developed by players solving problems in games. They can be rewarded with NFTs backed by tokens on a blockchain. A brilliant idea... from a Renaissance man who is also a medical doctor and the founder of a care marketplace for veterinarians. This is a fascinating one!  Listen and learn... The future of large language models  (LLMs) How ontologies can be crowd-sourced using games with NFTs as rewardsHow Synesis One is gamifying data yield farming with tokens on a Solana blockchainAbout the first graphic novel that is also an NFT-based sci fi gameWhy Paul selected  Solana instead of the more popular Ethereum blockchainHow to mitigate bias from entering ontologies generated by gamersReferences in this episode:Synesis OneMind AIQuantum NoesisEdmundo Gonzalez from Marpai Health on AI and the Future of Work 

Phil Johnson, founder and CEO of Master of Business Leadership (MBL) and veteran tech exec, overcame adversity as a kid when he was diagnosed with dyslexia. Phil taught himself to learn differently. He has helped organizations generate more than $1.5B by teaching leaders how to improve their emotional intelligence.Listen and learn...Why emotional intelligence is the most important skill for leaders.Why Phil says leaders battle our "500 million year old brain that doesn't like change."What Phil means by this: "we're the virus on the planet and we need to adapt to change to survive as a species."Why toxic environments are leading to record low employee engagement that is costing businesses over a trillion dollars per year.What Phil means by "we're born with an unconscious mind that gets wired as we grow to form habits."How leaders can endure pain and channel passion to get more energy and feel more motivated.How Apple's hiring practices and Putin's invasion of Ukraine are related.Questions to ask to hire candidates with the highest EQ.References in this episode...Matt K. Parker on AI and the Future of Work discussing "radical enterprises"The Master of Business Leadership program

Dipanwita ("D") Das, Founder and CEO of Sorcero, is an award-winning technology entrepreneur and AI innovator.  She is the CEO & Co-founder of Sorcero, a venture-backed AI Saas product startup, focused on using AI and NLP to inform critical decisions to improve lives.  Prior to starting Sorcero, D was the founder & CEO of 42 Strategies, managing digital transformation projects for Richard Branson's Virgin United, Al Gore's Climate Reality Project, and Bloomberg Philanthropies. Listen and learn...Why D says "...doing something that leaves a legacy of good" is a core element of Sorcero's mission.What D means by "...humans plus AI is greater than humans alone."How Sorcero strives to "accelerate vs. automate" decisions.How Sorcero helped doctors diagnose a rare form of metastatic breast cancer and save a life.What it means for patients that healthcare data is growing at a 36% CAGR.How Sorcero marries heuristics with NLP and transfer learning to help researchers. D's advice to females in male-dominated fields: "The only way to win is to persist."References in this episode...The Sorcero Life Sciences Intelligence PlatformD on TwitterPaddy Padmanabhan on AI and the Future of Work

Christopher Nguyen, serial entrepreneur and CEO of Aitomatic, realized big data isn't the only answer when training AI models. In fact, when doing preventive or predictive maintenance on industrial equipment, only small data is available. He and his team asked what if instead of relying on automated data collection we codify expertise in the heads of a small number of experienced technicians. And thus human-first AI was born. Aitomatic was launched in 2021 to productize the new field. It builds on Christopher's legacy of innovation having spent time in academia, at Google, and other startups including Arimo before its acquisition by Panasonic.Listen and learn...Why human-first vs. data-first AI may disrupt traditional approaches to machine learning.How automation problems in physical-first vs. digital-first industries require different solutions.How to build machine learning models when there isn t enough data.Why the world is in short supply of human expertise.How people feel about having their jobs automated away.Why the topic of ethical AI is controversial.The science behind neuromorphic computing.References in today's episode...AitomaticChristopher on TwitterGordon Wilson, CEO of Rain Neuromorphics, on AI and the Future of WorkThanks to Tess Hau from Tess Ventures for the introduction to Christopher! 

Matt K. Parker, author and engineering leader formerly at Pivotal Labs, profiled 13  collaborative work cultures in his book A Radical Enterprise. They're devolving control to employees and rethinking traditional organizational structures to give teams unprecedented levels of freedom. Not surprisingly, they're more successful than their peers. Listen and learn:What is a radical enterprise and what is radical collaboration?Why do employees do better work when they have freedom to define their own rules?What are the benefits of embracing the concepts of self-organizing and self-managing teams?Why do traditional performance management techniques like annual reviews create implicit threats in the workplace that demotivate employees?What does it mean to make every employee "a company of one"?Why, according to Deming, "a bad system will beat a good employee every time."References in this episode:Matt's website and a link to his Slack communityA Radical Enterpise published by IT RevolutionGary Bolles on AI and the Future of WorkJason Corsello from Acadian Ventures on AI and the Future of WorkTurn the Ship Around by L. David Marquet

Jaime Ramirez, CEO and Founder of Preventor, and stalwart of the Miami tech scene, shares how banks and brands are using new authentication technology to make life online safer. Automating authentication to verify age and other personal attributes is cheaper than manual verification and also more accurate. The stakes are high if automated decisions are wrong.  Hear Jaime explain the best way to automate the process of verifying your age or gender with AI.Listen and learn:How banks are automating authentication processes to comply with know your customer (KYC) and anti-money laundering (AML) regulatory requirementsHow the US compares with other countries, specifically Latin America, when it comes to KYC compliance and enforcementWhen it's ok to use technology to automate identity verification vs. when humans need to interveneWhich forms of biometric data are most accurate for identity verificationHow to mitigate the risk of bias when using AI plus selfies to verify ageWhen we'll finally move beyond passwords for identity managementWhat's fueling the net outflow of tech talent from Silicon Valley to MiamiReferences in this episode:John Whaley from UnifyID on AI and the Future of WorkJaime's blog postsPreventorPrivy