The Data Chief

Description: 

Marni Baker Stein, Chief Content Officer at Coursera, joins host, Cindi Howson, and dives into  the impact of Generative AI on skills, diversity in tech, and the future of upskilling.

Key Moments: 

• The impact GenAI and the surge of learning demand (05:45)
• Why employers must prioritize AI literacy (10.32)
• The gender gap in AI learning and why it matters (19:40)
• Leveraging data to drive personalization and learner success (24:00)
• Predictions for the future of AI in the labor market (29.53)

Key Quotes:

• “Generative AI is going to require us to all be a lot more emotionally intelligent because it's going to create such disruption and change. And we're all going to have to navigate the complexities of this change. We're going to have to bring our organizations through this change. That's going to take emotional intelligence as the one thing this technology isn't, is human. Understanding and human empathy is going to remain paramount.”
• “In terms of data and AI skills, what is extraordinary is that the demand for these skills in the last year has grown over a thousand percent. We now have seven individuals a minute enroll in GenAI content.”
• “Millions of people globally are deciding that it's time to upskill and reskill in these AI, regardless of whether their employer is telling them to or not. People see it happening. They're reading about it. They're hearing about it. And they're actively going out and chasing down those skills.”

Mentions:  

• Caste: The Origins of Our Discontent by Isabel Wilkerson
• From Academia to EdTech: The Path to an Equitable Education in the Digital Age 
• Girls Who Code

Marni Baker Stein Bio: 

Marni Baker Stein is Coursera’s Chief Content Officer, where she oversees the company’s content and credential strategy and partner relationships. Marni has more than 25 years of experience in producing and scaling online and hybrid education programs. Prior to joining Coursera, she was Chief Academic Officer and Provost at Western Governors University, where she led its four colleges serving more than 135,000 students with programs that improved access and affordability without compromising academic quality. Before that, Marni held several leadership positions focused on access, student success, and program design at institutions such as the University of Texas, Columbia University, and the University of Pennsylvania. She earned her PhD in Educational Leadership from the University of Pennsylvania. 

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Key Moments

• From Engineer to Data Leader (03:05)
• A Mindset Shift: Business Problem First, Data Second (9:31)
• Learning From Missteps (11:00)
• The Gazelle and the Lion Analogy (14:53) 
• The Role of AI: Do Things, Do Things Better, and Do Better Things (25:58)
• Built to Last versus Built to Adapt (40:01) 

Key Quotes

• "Instead of a data-first mindset, you need to have a business problem-first and data-second mindset. That has helped me transform myself as a leader quite a bit."
• "It’s more important to define the problem right than solving the problem. How can we understand what you’re trying to solve, and how it impacts the stakeholder?"
• “The head of data analytics functions need to be business problem driven, empathy driven, and not technology-first minded or AI-first minded. Our objective is to solve the business problems of the organization. Data, AI, and tech are the enablers.”
• "In the past, we built capabilities to last. Now, the mindset has to be to build capabilities to adapt."

Mentions

• Is Data Quality the Biggest Threat to Humanity? With Barr Moses and Olga Maydanchik
• Responsible AI Institute
• Two-Pizza Rule
• Girl Scouts STEM Classes
• From Cancerman to Ironman: A Police Officer's Journey of Arresting Illness
• Hans Zimmer

Deepak Jose Biography 

Deepak Jose is Vice President, Head of Data Sciences & Business Intelligence at Niagara Bottling. He is a member of the Forbes Tech Council, AWS Retail and CPG Executive Advisory Forum, industry standards associations, Editorial Board for CDO Magazine, and an advisor for startups and AI analytics service companies.

Before Niagara, Jose was part of global brands like Coca-Cola, Mars, ABB Group, Asurion and Mu Sigma in strategic roles driving business growth. He was named to the 2023 Consumer Good Visionaries by Consumer Goods Technology and Retail Info Systems News, the 2023 40 under 40 by CDO Magazine, the 2022 and 2023 Top 100 Innovators in Data & Analytics by Corinium Global Intelligence, the 2023 100 Most Influential AI Leaders in USA by AIM Research, the 2023 Direct 60 List by The Lead, and the 2023 DataIQ 100 lists.

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Key Moments: 

• Disappointment With Today’s AI Systems (4:00) 
• Congressional Inaction And The Need for AI Regulation (9:00)
• The Seduction of AI Propaganda (15:00)
• The Misguided Hypothesis of "Scale is All You Need" (23:00)
• Don’t Be Fooled by the Masters of AI Hype (27:00) 
• The Global AI Race and the Need for International Cooperation (33:00)

Key Quotes:

• “This matters. It matters as much as immigration policy or financial policy. The tech policy that we set right now is going to really affect the rest of our lives.”
• “We should want to have AI that can be like an oracle that can answer any question. There is value in trying to build such a technology. But, we don't actually have that technology. A lot of people are seduced into thinking that we do. But it may be decades away.”
• “Nobody can look you in the eye and say, ‘I understand how human intelligence works’. If they say that, they're lying to you. It's still an unexplored domain.” 

Mentions:  

• Taming Silicon Valley: How We Can Ensure AI Works for All Of Us 
• Kluge: The Haphazard Construction of the Human Mind
• The Algebraic Mind: Integrating Connectionism and Cognitive Science (Learning, Development, and Conceptual Change)
• The EU AI Act
• AI Generates Covertly Racist Decisions About People Based On Their Dialect

Dr. Gary Marcus Bio: 

Gary Marcus is a leading voice in artificial intelligence. He is a scientist, best-selling author, and serial entrepreneur (Founder of Robust.AI and Geometric.AI, acquired by Uber). He is well-known for his challenges to contemporary AI, anticipating many of the current limitations decades in advance, and for his research in human language development and cognitive neuroscience.

An Emeritus Professor of Psychology and Neural Science at NYU, he is the author of six books, including, The Algebraic Mind, Kluge, The Birth of the Mind, the New York Times Bestseller Guitar Zero, and most recently Taming Silicon Valley: How We Can Ensure AI Works for All of Us.  He has often contributed to The New Yorker, Wired, and The New York Times.

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Key Moments: 

Jeremy Kahn

• The history of AI: the Turing Test and the Eliza Effect with Jeremy Khan (1:50)
• Jeremy’s view on how we can learn from lessons of the past (9:00)
• It starts with data and people: leveraging AI to increase productivity (16:00)

Sol Rashidi

• Sol Rashidi on failing to succeed in AI (31:00)
• The need for rogue executives (37:00)
• Sol’s view on prioritizing GenAI use cases and measuring ROI (42:50)

Bernard Marr

• Bernard Marr on demystifying AI (60:02)
• Is society ready for AI’s impact on augmenting jobs? (66:00)
• AI’s impact on personalization of medicine, treatment and drug discovery (72:00)

Key Quotes: 

Jeremy Kahn

• “We're in a position where we can take action while this technology is still being shaped, to try to set some sensible guardrails. If we do that, we will see a lot of benefit from this technology. If we wait, we’re going to be in a situation like with social media. We will have a deskilling of essential human cognitive abilities.”
• We don’t talk enough about how to train people to use AI software. The organizations that think hardest about that are going to be very successful.”

Sol Rashidi 

• “Usually I start the conversations of how ROI shouldn't just be a financial measure. There's three ROI's in my opinion. There's a financial ROI, there's a cultural ROI, and there's a relevancy ROI.”
• “I am adamant that business value is not the number one marker. Everything needs to be scored and graded by criticality and complexity. And your criticality is a measure of ‘what is the impact if we don't do this?’”

Bernard Marr

• “What we are seeing is we will see an augmentation of pretty much every single job. I can't think of many jobs that will not be augmented by GenAI. We need to really expect change as individuals.”
• “We must create a world where education is seen as something that never stops, that carries on. I believe that we are currently entering a hyper evolution cycle, with artificial intelligence right at the center of it.”

Mentions: 

'Mastering AI: A Survival Guide to Our Superpowered Future' by Jeremy Kahn 

'Your AI Survival Guide: Scraped Knees, Bruised Elbows, and Lessons Learned from Real-World AI Deployments' by Sol Rashidi

'Generative AI in Practice: 100+ Amazing Ways Generative Artificial Intelligence is Changing Business and Society' by Bernard Marr

Bios: 

About Jeremy Kahn 

• Jeremy Kahn is an award-winning journalist for Fortune magazine, where he covers AI and other emerging technologies. Previously, he wrote about technology, including AI, for Bloomberg. His writing on a range of subjects has also appeared in The New York Times, Newsweek,The Atlantic, Smithsonian magazine, The Boston Globe, The New Republic, and Slate. An Ohio native, he now lives with his family in Oxford, England.

About Sol Rashidi

• With 10 patents granted and winning numerous awards that include: 'Forbes AI Maverick & Visionary of the 21st Century', 'Top 100 People in AI', 'Global 100 Power List', 'Top 75 Innovators', 'CAO of the Year', 'Top 5 CDO's', 'Top 65 Most Influential Women', Sol Rashidi is an seasoned executive, leader, and influencer within the AI, data, and technology space. Sol’s experience comes from real-world deployments where she has had to roll up her sleeves and do the work, while keeping the strategic intent in mind. Sol is currently Head of Technology for Startups, North America, at AWS.

About Bernard Marr

• Bernard Marr is a multi-award-winning and internationally best-selling author of over 20 books, who writes a regular column for Forbes and advises and works with many of the world’s best-known organizations. He has a combined following of 4 million people across his social media channels and newsletters and was ranked by LinkedIn as one of the top 5 business influencers in the world.

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Key Moments:

• The road to entrepreneurship (1:00) 
• Bringing transparency to the prescription drugs industry (4:30) 
• Analyzing in-game sports data to shoot for new heights (20:00) 
• Changing the world by making data and AI accessible to everyone (25:00) 
• How LLMs can build curiosity for the next generation of tech talent (33:00)

Key Quotes:

• “As with all things technology, everybody has access to the information, but few people take the time. But those who do tend to have an edge. If you're curious, if you love to learn, you're going to do pretty well. But how do you find those people when they're kids and how do you try to just capture their imagination and get them excited about the technology? That's why we started the bootcamp.”
• “I wanted to make technology accessible to people who otherwise couldn't get it. It doesn't matter what you look like, who you are, what your ethnicity is, what your background is. There are just going to be people who don't have access. I wanted to open that door for them. I'm a big believer in diversity, and that when you look at places where other people aren't, that's when you find brilliance that can change the world.”
• “The path to least resistance to learning AI is simple. All you’ve got to do is use it. You can use it in ways that you can’t possibly imagine. You can learn how to use large language models to start your own programming and teach yourself how to do it. The sky's the limit. Better way to put it, there is literally next to nothing you can't teach yourself using a large language model. You can even train and educate the model. It’s a virtuous cycle. It can surge curiosity with kids.”

Mentions:

• Cost Plus Drugs
• The Master Algorithm: How the Quest for the Ultimate Learning Machine will Remake our World 
• Mathletics: How Gamblers, Managers, and Sports Enthusiasts Use Mathematics in Baseball, Basketball, and Football 
• Mark Cuban AI Bootcamps

Mark Cuban Bio: 

Mark Cuban has been a natural businessman since age 12, when he sold garbage bags door to door.  He went on to found MicroSolutions right out of college, selling it to H&R Block.

From there he became an active stock trader, building a track record, starting a hedge fund and selling it a year later. In 1995, he and Todd Wagner started the first commercial streaming company, AudioNet, which became Broadcast.com. They later sold the company in 2000 for 5.7B dollars.

Mark acquired the Dallas Mavericks in 2000.  The Mavs competed in their first NBA Finals in 2006, won their first League title in 2011.  Mark sold majority ownership in 2023, but still retains a significant stake. During his time as majority owner, the Mavs had the second best record in the NBA.

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Key Moments:

• Why is the data wrong? (6:00)
• Our products are our data (11:00)
• The true size of the data quality problem (14:00)
• Clean your data before you prioritize shiny new tools (26:00)
• The next frontier: GenAI and unstructured data (31:00)

Key Quotes:

• “The data estate has changed significantly. But the way in which we manage data and data quality specifically has not adapted.” – Barr Moses
• “I tracked every single change in the data that I made, and could calculate how much money a company saved after a data cleanup. For a mid-size company, the difference was approximately a quarter of a billion dollars. For a large company, it could be several billion dollars. 45% of the data I cleaned had errors.” – Olga Maydanchik
• “The competitive advantage is really the access to your proprietary data that you have as an enterprise. So you need to make sure that that data is accurate, reliable, and on time. Now, how do you do that? That's something that people are still figuring out.”  – Barr Moses

Mentions:

• Information Quality Applied: Best Practices for Improving Business Information, Outcomes and Systems: Book by Larry English
• The Rest is History Podcast
• Freakonomics Podcast
• The Matrix Film Series
• The Play That Goes Wrong

Bio: 

Barr Moses: 

Barr Moses is the CEO and Co-Founder of Monte Carlo, the data reliability company. Monte Carlo is the creator of the industry's first end-to-end Data Observability platform. She is also co-author of O'Reilly's Data Quality Fundamentals: Building Reliable Data Pipelines. Previously, she was VP Customer Operations at Gainsight, a management consultant at Bain & Company and served in the Israeli Air Force as a commander of an intelligence data analyst unit.

Olga Maydanchik:

Olga Maydanchik is a data governance, data quality, and data architecture thought leader and practitioner. She is an expert in design and implementation of enterprise-wide data management programs, who has led data quality efforts at Deutsche Bank, AIG, and at Citi.

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Key Moments:

• Leveraging data for good (2:00) 
• Every leader is responsible for data management (13:00) 
• New metrics to validate AI’s sustainability (21:00) 
• Mitigating AI’s risks to society (23:00) 
• The current shape of global AI regulation (28:00) 
• The importance of diversity in mitigating data bias (37:00) 

Key Quotes:

• “Every leader must understand that they have a responsibility for data management. It’s an underlying skill that we really have to harness in all of our college, university, and high school programs. It's fundamental. We seem to teach people how to problem solve, but this is table stakes. In order to ever get AI right, we've got to solve the data challenges.”
• “There's no question on whether business value and how to measure AI’s return on investment (ROI) is always top of mind in my discussions with executives. But what they really want to know is if their existing ROI methods are sufficient or not. What are the new metrics that they need to put in place to validate AI and its sustainability?”
• “We’re not at the high-growth stage of AI innovation. We’re in the early experimentation stage. We don’t have international guardrails. All of these systems are going to take around 20-years to put in place. It takes six years to put a new university curriculum in place. People have to take responsibility to learn. This is a fundamental shift and it's one that's happening at break lightning speed.”

Mentions:

• Mood Insights
• Gallup Research: 1 in 5 Employees Feel Lonely Worldwide 
• KFF Loneliness and Support Networks Survey 
• United States Artificial Intelligence Institute 
• Dr. Cindy Gordon’s AI Insights Newsletter
• Hispanic Alliance for Career Enhancement and SalesChoice Whitepaper: Why Diversity Equity and Inclusion Leaders Must Lead in AI

Bio: 

Dr. Cindy Gordon ICD.D. is the CEO of SalesChoice, a SaaS AI company focused on Ending Growth Uncertainty for Human Advantage, and has been recognized by Onalytica as one of the top AI global influencers. Prior, she has held senior executive and partner roles at Accenture, Xerox, and Citicorp. She has also been a venture capitalist and angel advancing B2B technology software companies. Internationally, she is recognized for her innovative thought leadership with over 14 books in the market. Cindy is also a board advisor, thought leader in SaaS, AI and AI education, market research companies at: The AI Forum, Corent Technology, Forbes, Kaji.AI, USAII. Her AI community track record is extensive, University of Arizona – Business and Technology AI Board Advisor, Adjunct Professor, George Brown College, Applied AI. She regularly speaks at international conferences to advance AI Ethics and AI Education to board directors and C-suite executives. Academically, Dr. Gordon has an honorary Applied AI Doctorate Certification from George Brown College, an MIT AI Strategy Certification, and a doctorate in Complexity Science and Social Networks. She is also a certified Board Director with an ICD.D. designation. Under Dr. Gordon’s leadership, the company has won over twenty international awards, most recently she was recognized as the CEO of the Year Award for Women in Digital Transformation. She has also received the Governor General Award for her Innovation and Community Leadership.

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Key Moments: 

• A journey from intern to CEO (05:10)
• Encouraging a harmonized relationship between humans and AI (09:58)
• Why embracing stress can drive urgency and effective change (17:18)
• Generative AI’s impact on the skills landscape (30:39)
• Fostering a data-driven company culture (36:41)
• Embrace change, and quickly (40:25)

Key Quotes: 

• “AI does amazing things, like summarizations and semantic search. Humans do amazing things like curation of knowledge, making sure it's accurate, connecting the dots, and creating relationships. So bringing the power of humans-in-the loop, especially given a broader trust deficit, felt like the right thing to do at this point in time.”
• “I think ultimately what guides us is we want to be useful to our users and our customers. That's the guiding light. Because why do we exist as an organization or a community? We should all just go home. If we don't actually have a mission and purpose that adds value, then we don't have a purpose. So the question is, what is that? What is the highest purpose?”
• “When you think about the future of software development, there’s a lot of doomsdayers about job losses. I think it's going to be the opposite. I think AI reduces the barrier to entry. I think a lot of people will be “developers”, even though they may be doing very different things.”

Mentions: 

• WeAreDevelopers World Congress 2023 
• OverflowAI
• Overflow API 
• Stack Overflow for Teams
• Amp It Up Book 

Bio: 

Prashanth Chandrasekar is Chief Executive Officer of Stack Overflow and is responsible for driving Stack Overflow’s overall strategic direction and results.Prashanth is a proven technology executive with extensive experience leading and scaling high-growth global organizations. Previously, he served as Senior Vice President & General Manager of Rackspace’s Cloud & Infrastructure Services portfolio of businesses, including the Managed Public Clouds, Private Clouds, Colocation and Managed Security businesses. Before that, Prashanth held a range of senior leadership roles at Rackspace including Senior Vice President & General Manager of Rackspace’s high growth, global business focused on the world’s leading Public Clouds including Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP) and Alibaba Cloud, which became the fastest growing business in Rackspace’s history. Prior to joining Rackspace, Prashanth was a Vice President at Barclays Investment Bank, focused on providing Strategic and Mergers & Acquisitions (M&A) advice for clients in the Technology, Media and Telecom (TMT) industries. 

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Key Moments: 

• The emotional temperature for change in analytics (5:06)
• There’s no playbook for change management (7:53) 
• Why Generative AI success requires a melding of expertise (17:20) 
• Measuring the success of LLMs (18:58) 
• How do you embrace the new when you’re facing technical debt? (33:27)
• How to fine-tune your career in today’s data and AI landscape (37:30) 

Key Quotes: 

• “Business intelligence tends to have this notion of looking backwards. It's not thinking about prescriptive or predictive analytics, or live analytics, powered by the new capabilities that we're seeing. I do think we're going to evolve to a new name.” (03:42) 
• “You’ll find companies that were and are ahead of the curve will be able to take advantage of these new technologies, GenAI, LLMs, et cetera, much more quickly than other companies. So companies that have not invested the time, resources, money, attention, and prioritization into data governance, data use, and data literacy are at a serious disadvantage. And companies that have done the opposite, that have proactively invested, will be able to make significant gains.”
• “I think there's three pillars of success. One is understanding your data from end to end. What is it used for? What domain is it in? Understand it as much as possible. What is the product? What is the data product that you have in all aspects of it? Then, understand your business, right? How does data relate to your business? These people are going to be the ones that leverage the technology the most efficiently.”
• “Don't hesitate to take a lateral mobility move. I know people are always interested in going up, up, up, up, and up. However, you know, sometimes consider going sideways.” (40:46) 

Mentions: 

• Jamie Dimon Annual Shareholder Letter 
• Data Literacy 
• Data Storytelling 
• Unfrosted Film 
• Hacks TV Show
• Abraham Lincoln 

Bio: 

Scott Stevens is responsible for Intelligent Solutions, which empowers JPMorgan Chase employees through innovative data, Business Intelligence and low-code capabilities.

Scott has been with JPMorgan Chase since 2011 and has worked in Financial Services his entire 32-year career, with prior roles at MBNA, Bank of America and Sallie Mae. Scott has been in data and analytics roles since 1997.

Scott enjoys working with local universities on modernizing data science curriculum, guest lectures and coaching student teams on analytics projects.  While at work, Scott enjoys mentoring and likes to help people advance their careers and skills.  Scott serves on multiple non-profit boards, and Scott is the executive sponsor for the JPMorgan Chase Delaware Volunteer Leadership Group.

Scott lives in Delaware with his family. Scott’s personal interests include travel, wine-making, photography and rooting for the Philadelphia Eagles.

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Key Moments: 

• Leveraging Generative AI for work? Start by asking the right questions (04:13) 
• What’s in store for the future world of work (18:18) 
• How Generative AI can expand humans’ divergent thinking (26:16) 
• Taking people and culture along the Generative AI journey (31:20) 
• The value of diversity in data (42:00)
• A tale of mentorship (44:20)

Key Quotes: 

• “With Generative AI, now we have a command line interface that’s allowed us to converse, which is so core and essential to who we are as humans. The ability to be able to talk to one another. That's allowed us to survive for thousands and thousands of years and evolve.”
• “I think that there's a lot of greater potential in terms of expanding our own creativity and strategic thinking. So while humans have flexible and moldable brains and we have neuroplasticity that allows us to learn new things, we have to put ourselves in those environments. AI is really good at divergent thinking. So when we think about creativity, a core aspect of that is divergent thinking. What comes to mind when you think of a tree? Maybe leaves and fruit. Divergent thinking is thinking of all the outside things, like sunshine and soil, that may be associated with the tree or that tree growth. There's a lot more potential that we've yet to unlock in terms of updating our own thinking to expand our own divergent and creative thinking” 
• “We know that when we have more diverse teams where everyone feels that they can speak up, and you get better ideas. You get more collaboration. So having that core vision of what is that culture and environment that you want to have is really key” 

Mentions: 

• Women in Data
• Human Machine Collaboration Institute 
• Beyond AI Exposure: Which Tasks are Cost-Effective to Automate with Computer Vision?
• Dialect Prejudice Predicts AI Decisions About People’s Character, Employability, and Criminality
• AWS: What Are AI Agents?
• Women in Data Climate Sustainability Datathon 2023 
• The Creative Way: A Way of Being

Bio: 

Sadie St. Lawrence  is on a personal mission to create a more compassionate and connected world through technology. Having grown up on a farm in Iowa she witnessed first-hand how advancements in technology rapidly changed how we work and earn a living, which in turn affected the overall success of a community. In addition, Sadie was homeschooled her entire childhood which led to a unique perspective in self-directed learning approaches and out of the box thinking.

Sadie holds a diverse education having degrees in piano performance, psychology, and data science, but at her core she has always been a teacher. In 2014 she transitioned from working in a neuroscience lab studying emotional learning and memory, to working in data science. During her time as a data scientist, she went on to lead data science teams and consult for Fortune 500 companies in AI. Through her work, she noticed that while many organizations and individuals have good intentions when it comes to D&I in data careers, there was a lack of progress.

Today, Sadie’s work is focused on educating individuals in technology, increasing access and pathways for all people and creating a more equal future for all.

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