AI and the Future of Work
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Episode Number : 127
Krish Ramineni , Fireflies CEO and Microsoft alum, learned the value of NLP working with Skype and Office as a Product Manager. He set out to solve a problem he had: note-taking in meetings and following up afterward. Fireflies has been used by more than 60,000 organizations to make meetings more efficient. Krish has raised nearly $20M from an A-list group of investors including Canaan Partners and Khosla Ventures.
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- The evolution of speech recognition technology in the enterprise
- How Krish and the team build an AI voice assistant that joins meetings in 100 countries every day
- How to start with 85% ASR (automated speech recognition) accuracy and make it better using AI
- How to mitigate the impact of biased training data where foreign accents and uncommon speech patterns are underrepresented
- Who owns voice transcripts used to train AI models
- How being recorded changes participant behavior in meetings
- The future of “voice-first” computing
References in this episode:
- Krishna Gade from Fiddler discusses AI explainability
- Fireflies on Twitter
- A whole breast, AI-based ultrasound system was cleared by the FDA to improve mammogram accuracy
- Krish Ramineni, Fireflies CEO and Microsoft alum, learned the value of NLP working with Skype and Office as a Product Manager. He set out to solve a problem he had: note-taking in meetings and following up afterward. Fireflies has been used by more than 60,000 organizations to make meetings more efficient. Krish has raised nearly $20M from an A-list group of investors including Canaan Partners and Khosla Ventures.
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Episode Number : 126
Joel Eagle , McDonald’s Senior Director of Technology and Architecture, started his career in healthcare and logistics before being promoted to technology leadership roles at one of the world’s most iconic companies. Joel and his team manage the cloud infrastructure that powers 40,000 restaurants for two million employees… and helps serve happiness in 120 global markets to the equivalent of the world’s population every 100 days. The technology that makes McDonald’s work is phenomenally complex. Joel makes it sound simple. Hear from the expert. Oh, and stick around to the end for McDonald’s fun facts!
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- How Joel channels Ray Kroc’s vision when architecting systems: “restaurants should run themselves… it should be as simple as a shoebox with money going in and going out.”
- Why Joel says “if it’s easier for the crew it’s better for the consumer.”
- How AI, wearables, IoT, and AR are all parts of the McDonald’s technology vision.
- Why the shift supervisor at a McDonald’s restaurant has one of the hardest jobs in the world.
- The anatomy of a McDonald’s restaurant: “…they’re mini factories run by a server.”
- How AI is improving the drive-thru experience and personalizing the dining experience.
- What’s required to support the McDonald’s app which generates 16% of the company’s revenue and is the world’s most downloaded food ordering app.
References in this episode…
- McDonald’s by the numbers
- Meta Research is improving NLP accuracy with less training data by using our understanding of how humans learn languages
- Giselle Mota, TEDx speaker and top 100 “Future of Work” thought leader, on AI and the Future of Work
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Episode Number : 125
Ben Brennan , QSTAC CEO, author, and former IT exec at Yahoo and Verizon Media, is a world traveler, a musician, and a trained psychologist with passions for philosophy and psychotherapy. Not exactly the traditional background for an IT leader. Early roles at Pivotal Labs and Jawbone taught Ben that bringing humanity to technology is the future of work. He since published Badass IT Support and started QSTAC to measure the employee experience.
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- What Ben learned managing 100 people and supporting 15,000 employees at Yahoo
- How the culture at Pivotal Labs inspired Ben’s philosophy on quantifying the employee experience
- How Ben convinced a former Apple leader why QSTAC is better than NPS
- Why CSAT scores don’t actually correlate with how satisfied employees are at work
- How the principles of Design Thinking can be used to run IT
- What IT must do to avoid being “Uber-ed” like the taxi industry
References in this episode…
- Dion Hinchcliffe on AI and the Future of Work
- Tim Crawford on AI and the Future of Work
- Matt K. Parker on AI and the Future of Work
- O’Reilly’s 2021 AI adoption in the enterprise survey
- QSTAC
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Episode Number : 124
Francois Candelon , Managing Director at the BCG Henderson Institute, has spent 30 years researching how companies adopt modern technology. His research spans business, technology, economics, and science. Francois is a popular speaker, author, and advisor who has been featured at events including Mobile World Congress, TED@BCG, Politico AI Summit, and Wuzhen Internet Conference. Francois is also a leader on BCG’s GAMMA AI@Scale team.
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- The one company Francois says best illustrates how AI can transform legacy industries
- Why “artificial intelligence” isn’t really “intelligent”
- What is an “AI strategy”… and what are the four questions to ask to define yours
- How a fintech company in the UK reduced costs to transfer money by 90% with AI
- What’s required to earn the public’s trust in AI
- Why every company should be required to have a “social license” to use AI
References in this episode…
- Fortune article on human-machine collaboration by Francois
- Francois’ “BCG Expert” profile
- Eric Daimler, Obama’s AI authority, on AI and the Future of Work
- The McKinsey “AI in 2020 Survey”
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Episode Number : 123
Stephen Messer , founder of Collective[i], was an attorney and teacher before discovering his passion for entrepreneurship. He started LinkShare (acquired by Rakuten in 2005) which made it possible to pay for clicks on the web. He changed how the web works and now he’s using AI to change the world of B2B sales. The world needs more visionaries like Stephen. Hear what fuels him and learn about his process for disrupting legacy industries.
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- The four words that define what all the best entrepreneurs do better than everyone else
- Why sales is the only job function where “30% productivity is the norm”
- What’s required to use AI to help B2B sales people
- How to use RPA to automatically update CRM systems
- How Stephen’s winning against Salesforce, Microsoft, and HubSpot
- What to look for in a mentor
References in this episode…
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Episode Number : 122
In this special episode, we unpack the controversy surrounding the sentient chatbot that “worries about its future”. Google engineer Blake Lemoine published a transcript of a conversation with the chatbot LaMDA that generated strong reactions from technologists and AI ethicists. It conjured images from science fiction movies that always capture the public imagination.
Show moreShow lessTiernan Ray, ZDNet writer, accomplished tech journalist, and good friend of the podcast, joined host Dan Turchin to reflect on the story based on his analysis of the 5,000-word LaMDA transcript.
Listen and learn…
- What will it be like to co-habit a world with thinking machines?
- What does it mean for an AI to be sentient? Why should we care?
- Should AI be protected under the 13th amendment?
- How do we know LaMDA’s not sentient from the transcript?
- What are the ethical implications of developing sentient bots?
- Did Google act responsibly in developing a bot that is sentient-like?
References in this episode…
- Tiernan’s analysis of the LaMDA transcript
- Melanie Mitchell on MSNBC
- Blake Lemoine’s interview with Steven Levy in WireÂ
- Alan Turing’s Imitation Game
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Episode Number : 121
Kevin Dewalt , CEO of Prolego, built his first neural net at Stanford in 1995 after graduating from the U.S. Coast Guard Academy. He popularized the term “AI abundance” to describe the path of exponential technologies and how AI adoption is five years from becoming mainstream. He now applies 25 years of studying AI to help organizations embrace the future.
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- What every company needs to know to succeed with AI.
- How the most successful organizations approach AI investments.
- Why Kevin says: “…we haven’t had a single project where we’ve used AI to eliminate jobs.”
- What Kevin feels is the most disruptive field within AI research.
- Practical applications of NLP and large language models (LLMs)
- Kevin’s contrarian view on AI ethics
References in this episode:
- The world’s first AI comic book
- Kevin’s book: Become an AI Company in 90 days
- Kevin’s company: Prolego
- Snorkel to automate data labeling
- Andrew Yang on AI
- “D” Das, Founder and CEO of Sorcero, on AI and the Future of Work
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Episode Number : 120
Giselle Mota , Future of Work principal at ADP, overcame dyslexia and discovered passions for math and AI. Her parents immigrated from the Dominican Republic and taught Giselle the power of perseverance. Now she speaks frequently to global audiences about the importance of using AI responsibly to hire and nurture talent.
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- How AI accelerates the process of learning new skills
- How to mitigate the impact of bias in automated decision-making
- The dangers of using facial recognition in recruiting and hiring processes
- How to design organizations that celebrate cognitive diversity
- How to optimize hiring processes to avoid confirmation bias
- How many jobs will be created by AI before 2025 according to the World Economic Forum
- Giselle’s coaching for females and under-represented minorities in STEM fields
References in this episode:
- Your $250 discount from Hello Landing using Giselle’s promo code: giselle_itg
- Bernard Marr, Futurist
- Joy Buolamwini, AI social justice advocate
- Bryan Talebi from Ahura AI on AI and the Future of Work
- Kai Nunez from Salesforce on AI and the Future of Work
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Episode Number : 119
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.
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- A better way to identify customer sentiment using supervised machine learning
- What techniques are most effective for labeling training data
- Why traditional methods of measuring customer satisfaction are poor at understanding actual customer satisfaction
- How to mitigate the impact of bias in training data
- How Harish defines “responsible AI”
- Why there will always be a need for human customer success managers
References in this episode…
- Emtropy Labs
- Chandra Khatri from Got It AI on AI and the Future of Work
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Episode Number : 118
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.
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- What it’s like to shift from academia to venture capital to entrepreneurship to public service
- How the growth of data sources as well as data creates an unimaginably large number of data relationships
- How Conexus applied categorical algebra to bring together 300k databases at Uber
- Why 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 make
- The challenges of enforcing data policies like GDPR in the EU
- How Eric defines “responsible AI”
References in this episode…
- Eric’s company, Conexus
- The President’s Council of Advisors on Science and Technology
- Aftershock which includes a chapter by Eric
- Eric on Twitter
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Episode Number : 117
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.
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- About the three waves of chatbot technology
- Why “more deflection” doesn’t need to translate into “lower satisfaction”
- How Calm uses Solvvy to deliver automated customer service
- Why AI based on semantic similarity is better than traditional scripted chatbots
- Why “putting the user first” and “not hiding the live agent” is essential for gaining consumer trust in chatbots
- How to address latent bias in data used to train AI models
- Why bots will never replace live agents
References in this episode…
- Rory O’Driscoll from Scale Venture Partners on AI and the Future of Work
- Solvvy acquired by Zoom
- Chandra Khatri from Got It AI on AI and the Future of Work
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Episode Number : 116
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.
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- 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 AIÂ
- Chandra on LinkedInÂ
- 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.
- Christopher Nguyen on AI and the Future of Work
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Episode Number : 115
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!
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- The future of large language models (LLMs)
- How ontologies can be crowd-sourced using games with NFTs as rewards
- How Synesis One is gamifying data yield farming with tokens on a Solana blockchain
- About the first graphic novel that is also an NFT-based sci fi game
- Why Paul selected Solana instead of the more popular Ethereum blockchain
- How to mitigate bias from entering ontologies generated by gamers
References in this episode:
- Synesis One
- Mind AI
- Quantum Noesis
- Edmundo Gonzalez from Marpai Health on AI and the Future of Work
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Episode Number : 114
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.
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- 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
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Episode Number : 114
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.
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- 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 Platform
- D on Twitter
- Paddy Padmanabhan on AI and the Future of Work
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Episode Number : 113
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.
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- 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
- Aitomatic
- Christopher on Twitter
- Gordon Wilson, CEO of Rain Neuromorphics, on AI and the Future of Work
Thanks to Tess Hau from Tess Ventures for the introduction to Christopher!
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Episode Number : 112
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.
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- 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 community
- A Radical Enterpise published by IT Revolution
- Gary Bolles on AI and the Future of Work
- Jason Corsello from Acadian Ventures on AI and the Future of Work
- Turn the Ship Around by L. David Marquet
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Episode Number : 111
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.
Show moreShow lessListen and learn:
- How banks are automating authentication processes to comply with know your customer (KYC) and anti-money laundering (AML) regulatory requirements
- How the US compares with other countries, specifically Latin America, when it comes to KYC compliance and enforcement
- When it’s ok to use technology to automate identity verification vs. when humans need to intervene
- Which forms of biometric data are most accurate for identity verification
- How to mitigate the risk of bias when using AI plus selfies to verify age
- When we’ll finally move beyond passwords for identity management
- What’s fueling the net outflow of tech talent from Silicon Valley to Miami
References in this episode:
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Episode Number : 110
Edmundo Gonzalez , Co-founder and CEO of Marpai Health, realized our health plans have a significant impact on the quality of our health. Using AI to predict who will need care and when can lead to better health care plans and a healthier population. Edmundo’s on a mission to make it easier for all of us stay healthy… which first requires the traditional healthcare system to be disrupted.
Show moreShow lessListen and learn:
- How to turn America’s “sickcare” system into a true “healthcare” system.
- How AI can make better decisions about who is likely to need care and when.
- How to use data to recommend treatment early to prevent significant, more costly procedures later.
- How to optimize deep learning models using patient data to balance accurately predicting who will need care (precision) with how many recommendations are made (recall).
- The ethical implications of using patient data to make healthcare decisions.
- Why Big Tech doesn’t own the future of healthcare.
References in this episode:
- Paddy Padmanabhan on AI and the Future of Work
- Marpai Health
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Episode Number : 109
Doug Kerwin is an engineering leader and entrepreneur who recently published “Riley and Bot: Jobs for Robots and Jobs for Me”. By day, he’s a Vice President of Cloud Engineering at Prudential. After hours, he’s a dad who wants the best for his daughter and needed to answer her questions about the impact of AI on jobs.
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- What inspired an engineer without an AI background to write a kids book about AI
- Why Doug concludes that “no job will be completely AI-resistant”
- New careers that are being created by the introduction of AI-related technology
- How GitHub Copilot is helping programmers write better code faster
- Which innately human skills will never be automated
References in this episode:
