Artificial intelligence is reshaping work, creativity, business, and society faster than ever before, but how worried should we really be?

In this episode, we sit down with The AI Doc producers Charlie Tyrell and Ted Tremper to discuss the biggest lessons they learned after spending years investigating AI and interviewing leading experts, including Sam Altman, Dario Amodei, Karen Hao, and many of the influential voices shaping the future of artificial intelligence.

The conversation goes far beyond the typical AI debate, exploring AI ethics, generative AI, creative industries, wealth inequality, AI regulation, AGI, automation, AI governance, and the growing question of whether artificial intelligence is an inevitable force—or a technology that society can still shape. Charlie and Ted discuss the risks of concentrated power, the impact of AI on artists and filmmakers, ethical AI development, transparency, consent, and what individuals can do to influence the future of technology.

AI is changing everything. The way we work, the way we create, the way we build businesses, and potentially the future of society itself. But beneath the headlines, hype, and fear, what’s actually true?

If you're interested in artificial intelligence, technology, leadership, innovation, creativity, or the future of humanity, this is a conversation you won't want to miss.

Like and follow for weekly episodes.

In this episode:

00:00 Intro

01:25 Why Charlie Tyrell & Ted Tremper made the film

02:20 The origins of The AI Doc

04:45 AI anxiety, parenthood & the future

06:57 Wealth inequality and AI concentration

08:17 Reasons for hope and concern

11:01 How individuals can shape AI's future

11:49 Why education creates agency

13:02 AI's impact on artists and creators

15:12 Did The AI Doc use AI?

16:56 Human creativity vs AI-generated content

18:14 The filmmaking industry's AI debate

19:20 Generative AI and storytelling

21:23 Audience demand and the future of human-made art

23:13 Technology's impact on creativity throughout history

24:50 Ethical AI, consent & compensation

27:02 Can AI ever be ethical?

28:12 Policy, regulation & AI accountability

30:59 The AI arms race explained

32:14 AI competition, China & global innovation

34:07 AI narratives we should question

35:00 The Myth of AI Inevitability

37:08 Democratizing AI and power structures

38:11 What AI advocates get wrong

40:40 Radical imagination & AI governance

42:45 What gives Charlie and Ted Hope?

46:22 Raising children in an AI world

51:56 Technology, optimism & intellectual humility

55:00 The most influential voices in AI

57:39 Karen Hao, Deborah Raji & human-centered AI

1:00:08 Responsible AI use for business leaders

1:02:13 Fighting over-optimization and AI dependence

1:04:19 The hidden risks of AI services

1:07:12 Final Thoughts

Connect with The AI Doc:

X: https://x.com/theaidocfilm

Instagram: https://www.instagram.com/theaidocfilm/

Our links:

Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast

Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Artificial Intelligence is changing faster than most people realize, but are we asking the wrong questions about AI, AGI, consciousness, and the future of society?

In this episode, cognitive scientist and AI researcher Joscha Bach joins us for a thought-provoking conversation on artificial intelligence, machine consciousness, large language models (LLMs), AGI, human intelligence, and the future of work.

Joscha explains why intelligence is fundamentally about model-building, why consciousness may be a biological training algorithm, and what current AI systems are still missing.

The conversation goes far beyond technology, tapping into innovation, capitalism, regulation, scientific progress, institutional trust, democracy, media narratives, AI safety, employment disruption, economic incentives, and the future of human civilization. Joscha shares his perspective on AI doom scenarios, why he believes many fears around artificial intelligence are overstated, and how AI could ultimately empower individuals rather than replace them.

This episode offers a different look into artificial intelligence, human progress, and what comes next.

Like and follow for weekly episodes.

In this episode:

00:00 Intro

01:04 AI doom scenarios & humanity's future

02:00 Defining intelligence & consciousness

05:00 Why AI intelligence is different from human intelligence

06:52 Are LLMs actually intelligent?

08:10 Why AI hallucinates

10:09 Human learning vs machine learning

11:22 Can transformers lead to agi?

12:28 The scaling hypothesis explained

13:58 Mechanistic interpretability & neural networks

15:13 Can AI surpass human understanding?

18:42 AI and the future of scientific discovery

20:14 Why scientific progress feels slower today

22:03 Institutions, incentives & organizational decline

25:05 Trust in government and society

28:31 Can AI improve democracy?

30:40 Why AI gets such negative media coverage

33:03 The AI extinction debate

36:30 AI, automation & the future of jobs

40:05 Big Tech, AI power & capitalism

41:15 Money, markets & resource allocation

46:28 Regulation, innovation & economic growth

49:13 Why innovation is slowing down

51:08 Is Big Tech starving other industries?

54:39 Is there an AI bubble?

57:30 Could the financial system be rebooted?

01:00:17 Cryptocurrency, regulation & economic stability

01:08:27 Regulation, governance & innovation

01:10:33 Lessons from Berlin's innovation culture

01:16:08 AI, surveillance & centralized power

01:18:07 Decentralized AI and individual empowerment

01:20:05 AI, healthcare & professional expertise

01:23:36 Control, society & human responsibility

01:25:00 Advice for leaders and innovators

01:26:03 Escaping filter bubbles

Connect with Joscha Bach:

LinkedIn: https://www.linkedin.com/in/joschabach

X: https://x.com/Plinz

Our links:

Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast

Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Modern work is broken.

Endless meetings. Constant notifications. Work invading every corner of life.

So, what does the future of work actually look like in the age of AI agents, generative AI, and organizational transformation?

Microsoft’s Head of Future of Work & AI, Matthew Loys Duncan, says we’ve reached “human capacity” and that AI may not replace knowledge workers, but instead replace the worst parts of work itself.

In this episode, Matthew joins Geoff Nielson to unpack how AI agents, generative AI, and organizational redesign are reshaping white-collar work. He explains why most companies are approaching AI the wrong way, why culture matters more than technology, and how the future of work will be “human-led, agent-operated.”

From Microsoft’s Work Trend Index research and AI-native organizations to tacit knowledge, burnout, productivity, and leadership transformation, this conversation explores what happens when businesses stop optimizing old workflows and start redesigning work from the ground up.

If you’re trying to understand the real impact AI will have on work, leadership, and business strategy over the next decade, this episode is for you.

Like and subscribe for weekly conversations on AI, business, leadership, and the future of work.

In this episode:

00:00 Intro

00:01:15 Will AI replace white-collar jobs?

00:02:29 Why AI is a reimagination of work, not doom & gloom

00:03:08 Human-led, agent-operated work

00:03:37 The broken reality of modern office work

00:04:36 Digital overload, meetings & workplace chaos

00:06:16 Human agency vs AI agents

00:07:33 Using AI to redesign your job

00:09:02 Why the best AI users don’t outsource judgment

00:09:49 Delegation, intentional AI use & skill preservation

00:10:54 AI as a team member, not just a tool

00:11:27 The four ways people use generative AI

00:14:10 The rise of AI agents in the workplace

00:16:16 From personal productivity to organizational transformation

00:17:10 Where is the ROI from AI?

00:18:02 Why AI adoption alone fails

00:20:13 Finding the highest-leverage AI opportunities

00:23:27 Re-architecting work in the AI era

00:25:27 Should employees build their own AI agents?

00:28:39 AI-native organizations vs legacy enterprises

00:30:05 AI adoption vs AI absorption

00:32:31 Discovering hidden business value through AI

00:33:27 How legacy firms can compete with AI-native companies

00:35:06 Why AI transformation starts with culture

00:36:05 The role of HR, CEOs & leadership in AI strategy

00:39:14 Why AI is bigger than a technology initiative

00:41:12 The expanding role of the C-Suite in AI transformation

00:46:32 Microsoft’s “learn it all” leadership culture

00:50:00 Democratizing innovation with AI

00:53:23 Tacit knowledge & AI-powered learning

00:57:09 Information retrieval, organizational knowledge & AI

00:59:37 Capturing institutional intelligence with AI

01:00:03 Advice for business & technology leaders

01:03:17 Why there is no AI playbook yet

Connect with Matthew:

LinkedIn: https://www.linkedin.com/in/matthewloysduncan/

X: https://x.com/matthewloys

Our links:

Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast

Follow us on YouTube: https://www.youtube.com/@InfoTechRG

What if the biggest threat from AI isn’t artificial intelligence… but the economic system controlling it?

Author and creator of the Lean Startup methodology, Eric Ries says many of the biggest fears around AI are actually fears about capitalism.

In this episode, Eric joins us to talk about why great companies lose their value over time, how shareholder prioritization reshaped modern business, and why AI could either amplify human creativity or become the ultimate cost-cutting machine.

He explains the hidden forces behind corporate corruption, the concept of “financial gravity,” and why companies like Costco continue to outperform despite rejecting many traditional Wall Street “best practices.” From private equity and governance structures to AI alignment and the future of human creativity, this conversation explores the incentives shaping business, technology, and society itself.

Like and follow for weekly episodes.

In this episode:

00:00 Intro

01:00 Why great companies “go bad”

02:10 The rise of corporate corruption

05:48 Is capitalism itself the problem?

07:08 Making money without creating value

10:33 Corporate accountability & human flourishing

13:06 Why this problem keeps getting worse

18:21 How investors destroyed FedMart

21:22 Why Costco defies wall street logic

23:00 Financialization & the collapse of institutions

24:27 How leaders can protect mission-driven companies

27:12 “Financial gravity” explained

31:10 Trustworthiness as a business asset

34:37 Governance structures that actually work

36:20 Transitioning into AI & the future of work

37:42 AI governance & Anthropic

38:37 The AI alignment problem

41:30 Why AI is being optimized for cost cutting

42:15 AI should augment creativity, not replace humans

44:04 How to use AI as a learning tool

46:34 Real examples of AI augmentation done right

49:47 AI-assisted reading & learning

50:22 The problem with AI-generated “slop”

54:58 Why human-made work will become premium

57:19 The future of the attention economy

59:12 Will AI become addictive like social media?

01:00:03 The case for an AI Bill of Rights

01:04:11 Costco, DEI & organizational integrity

01:07:13 AI Regulation, governance & human flourishing

01:13:24 Fighting the “normative consensus” of shareholder primacy

01:21:21 Is the era of shareholder primacy already over?

01:22:22 Final thoughts

Connect with Eric:

LinkedIn: https://www.linkedin.com/in/eries/

X: https://x.com/ericries

Our links:

Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast

Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Are we entering the most transformative era of work in history?

Technology is evolving weekly, and culture takes time to adapt. In this episode, AI futurist and award-winning innovation leader Maurice Conti explains how rapid technological change, especially in artificial intelligence, will shape our world, the economy, and the future of jobs, and what AI leadership means for navigating these shifts.

Drawing on his experience with companies like Amazon, Nike, Mercedes, and Lululemon, Maurice shares insights from Fortune 100 companies and explains how generative AI, automation, and human-AI collaboration are transforming the workplace.

The key insight is simple. The future of AI is not big, flashy, or “sexy.” It is quiet, invisible, and massively impactful. Maurice explains why we have entered the “Augmented Age,” where humans and AI work together, and outlines the major shifts known as the 4 Waves of AI defining this transformation, including the grassroots AI revolution happening inside organizations and the rise of AI agents and ecosystems.

If you want to understand where AI is really going beyond the hype, this is a must-watch episode.

Like and follow for weekly episodes.

In this episode:

00:00 Intro

01:04 The “Augmented Age”: Humans + AI working together

02:10 Sci-Fi to reality: Talking to computers like Star Trek

04:11 Have we arrived at intuitive AI?

05:15 Why AI progress isn’t linear

06:05 Can anyone predict the future of AI?

07:05 The Nvidia story & “more AI in the future” principle

08:57 Amara’s Law: Short-term hype vs long-term impact

10:08 Why AI will be bigger (and slower) than expected

10:54 The 4 Waves of AI explained

11:00 Wave 1: “Interesting but not useful” AI

12:31 Wave 2: Grassroots AI (hidden ROI inside companies)

13:16 Why CEOs can’t see AI ROI

14:09 Tool users → tool makers (the real shift)

16:17 The invisible productivity explosion

20:10 Wave 3: AI agents & ecosystems

21:48 Wave 4: AI as electricity (invisible & everywhere)

23:18 The dark side of “interesting AI”

26:15 Personal AI use cases (daily life & work)

27:09 Why most organizations are still “Grassroots”

28:38 The explosion of tools (new risks for IT)

30:15 CIO/CTO challenges: Control vs innovation

33:09 Building the right AI infrastructure layer

34:45 Where should companies invest in AI?

37:14 Start with the problem, not the technology

40:04 Toolset vs skillset vs mindset

42:45 Why mindset & culture matter most

44:28 The race to the bottom vs innovation

45:15 New workplace norms & ethical questions

49:49 Why culture changes slowly

51:33 Tech vs culture: A fundamental tension

52:30 Can organizations adapt to constant change?

56:06 The myth of big, sexy AI

57:01 Small AI, massive impact

58:18 Where real innovation is happening

59:13 Why young workers lead AI adoption

01:01:22 Advice for leaders

01:02:59 AI is a “Lord of the Rings” journey

01:05:15 Will AI replace jobs?

01:10:23 Lessons from past tech revolutions

01:13:47 Why humans need ~25 years to adapt

01:16:02 Why expectations rise with technology

01:17:38 Why there will always be more work to do

01:18:55 Final thoughts

Connect with Maurice:

LinkedIn: https://www.linkedin.com/in/mauriceconti/

Our links:

Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast

Follow us on YouTube: https://www.youtube.com/@InfoTechRG

What if everything we’ve been told about AI and the future of work is wrong?

John Hagel says most leaders are asking the wrong questions:

“How fast can we automate?”

“How many jobs can we cut?”

According to him, that’s a “going out of business strategy.”

In this episode, we sit down with Silicon Valley veteran John Hagel, an advisor to firms like McKinsey, BCG, and Deloitte, to challenge the dominant narrative around AI, automation, and job elimination. He shares insights into how leaders are approaching AI today, often focusing on cost-cutting and workforce reduction, and what that means for the future of business and entrepreneurship.

John explains that the real opportunity with AI isn’t efficiency, it’s learning. He talks about the shift from scalable efficiency to scalable learning and how organizations can use AI to augment human potential, unlock creativity and curiosity, and build cultures rooted in trust, collaboration, and continuous improvement.

If you’re thinking about the future of work, this episode will challenge how you view AI, strategy, and innovation, and offer a different perspective on AI’s role in the modern economy.

Like and follow for weekly episodes.

In this episode:

00:00 Intro

01:30 Is “this time different” with technology?

02:29 The Big Shift: Why organizations must fundamentally change

03:18 Scalable efficiency vs scalable learning

05:33 The dangerous AI narrative: automation & job cuts

06:19 Why efficiency alone leads to diminishing returns

09:42 Trust: The missing foundation in most organizations

10:50 What happens when companies fail to adapt

12:21 Debunking AI myths and media narratives

12:46 Humans vs machines: who should do what?

13:14 Reskilling vs building human capabilities

15:03 How to convince leaders to rethink AI strategy

16:24 Fear vs opportunity in leadership

20:16 What real workplace learning looks like

21:18 The future leader: asking better questions

24:38 How to structure high-impact teams

26:06 The collapse of trust in institutions

26:58 Corporate narratives & Apple’s “Think Different”

30:06 Creativity vs technology in strategy

30:41 Zoom Out, Zoom In strategy explained

33:08 Microsoft example: seeing the future early

35:14 Why agility without direction fails

37:21 Understanding “the edge” and innovation

39:34 Why transformation efforts fail in large companies

41:22 Scaling the edge vs top-down change

42:52 The power of the “explorer mindset”

47:18 Why companies suppress passion

48:31 Only 14% of workers are truly passionate

50:18 Can passion be cultivated at scale?

52:29 Does IT still matter in the AI era?

55:07 AI, healthcare, and the future of longevity

57:13 From healthcare to “wellness ecosystems”

58:19 The rise of the trusted advisor

59:50 Can AI replace human advisors?

01:02:25 Advice for leaders

01:04:18 AI is a tool humans determine its impact

01:06:29 Why most digital transformations fail

Connect with John:

LinkedIn: https://www.linkedin.com/in/jhagel/

X: https://x.com/jhagel

Our links:

Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast

Follow us on YouTube: https://www.youtube.com/@InfoTechRG

What if the AI revolution isn’t what we’ve been promised?

What does an economist and bestselling author have to say about the idea that Big Tech may be overselling the future of artificial intelligence?

In this episode, Oxford economist and Associate Professor of AI & Work, Carl Benedikt Frey, shares his skeptical perspective on the impact of artificial intelligence. He explains what it could mean for the future of work, including job market shifts and the necessity of skills development.

This conversation takes a critical look at the economic changes driven by AI, challenging the dominant narrative around productivity and technological progress. While Big Tech describes a future of abundance, Carl argues that history tells a more complicated story. From the Industrial Revolution to the computer age, breakthrough technologies didn’t automatically lead to sustained productivity or shared prosperity, and AI may follow a similar path.

Like and follow for weekly episodes.

In this episode:

00:00 Intro

00:57 Why the “AI Abundance” narrative might be wrong

01:45 Lessons from the computer revolution & productivity slowdown

03:30 AI vs computers: Automating cognition vs information

05:19 Why Big Tech may be overhyping AI impact

06:20 Automation vs creating new industries

08:08 AI infrastructure race: US vs China

10:25 The “Steam Engine Moment” AI hasn’t reached

12:31 Why technology alone isn’t enough

14:19 Why breakthrough innovation is declining

15:09 The collapse of business dynamism

15:45 Corporate lobbying, patents & barriers to entry

17:27 Why this matters more than AI itself

18:20 Startups vs Big Tech: Who drives innovation?

19:36 Will AI accelerate economic inequality?

21:37 Lessons from the Gilded Age & Antitrust History

24:04 Why strong governments enable competition

25:00 Big Tech vs historical monopolies

26:19 Centralization vs decentralization in innovation

29:01 Japan vs US

33:56 AI and the “more vs better work” problem

35:20 Will AI lower quality in research & knowledge?

36:23 AI: Increasing quantity vs improving quality

38:16 Why AI benefits low-skill workers more

39:49 AI and the rise of global labor competition

40:42 AI-driven offshoring

42:17 Which jobs are most at risk?

44:06 Long-term labor market predictions

46:20 Where humans still beat AI

48:15 The growing anti-AI backlash

49:11 Historical resistance to technology

53:39 Can government reduce AI disruption?

56:01 Why institutions determine outcomes

59:25 Advice for business leaders

01:00:12 Why decentralized companies win

01:02:24 Why innovation requires “waste”

Connect with Carl:

LinkedIn: https://www.linkedin.com/in/carlbfrey/

X: https://x.com/carlbfrey

Our links:

Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast

Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Why are 88% of businesses using AI but only 5% seeing real transformation?

In this episode, we sit down with Dan Diasio, EY’s Global Consulting AI Leader and CTO, to break down the four possible futures of AI, from constraint to full transformation, and what it takes for organizations to win in an AI-driven world.

Drawing from his experience advising Fortune 50 executives, Dan explains how leaders are navigating uncertainty, why many companies fall into the “sameness trap,” and what separates simple AI adoption from true competitive differentiation.

We also explore the rise of AI agents and end-to-end workflows, why mindset and skillset matter more than toolset, and what the future of jobs looks like in an AI-first world.

If you are thinking about AI strategy, leadership, or how to prepare your organization for what comes next, this episode delivers practical and forward-looking insights.

Like and subscribe for weekly episodes.

In this video:

00:00 Intro

00:40 Inside SXSW: Future-proofing AI strategy

02:14 Why predicting AI is impossible

02:56 The four AI futures explained (constraint → collapse)

04:36 What winning teams did differently

05:50 The “sameness trap” in AI

06:19 Positive vs negative AI futures

07:23 Constraint, growth, transform, collapse

09:54 What people actually believe about AI’s future

10:45 How do you win with AI?

13:17 Why business model innovation beats automation

14:02 Hands-on AI

15:46 How AI commoditizes output

17:01 AI investment trends: Productivity vs differentiation

18:13 The shift toward competitive advantage with AI

19:27 The AI Playbook: How leaders get it right

20:34 Going broad vs going deep with AI

21:11 88% vs 5%: The AI Adoption Gap

22:20 Mindset vs skillset vs toolset

23:27 Top-down vs bottom-up AI transformation

25:16 The visibility trap explained

26:06 Why new talent drives AI innovation

28:22 AI resistance & fear in organizations

29:43 “Death by a Thousand Papercuts” automation

30:54 New jobs: Knowledge Engineers & AI Orchestrators

32:48 Future Skills: Critical thinking, creativity, systems thinking

35:12 The role of IT in the AI era

37:34 AI as the new operating system of business

39:01 SaaS vs A

44:35 AI prototyping vs enterprise-scale systems

47:18 Will AI kill consulting?

54:07 AI infrastructure constraints & global risks

56:09 Biggest AI myths & misconceptions

57:34 Are we automating the wrong things?

59:27 Amara’s Law & AI hype cycles

01:00:12 How leaders should prepare

01:01:01 Why value creation beats cost cutting

01:02:17 Aligning AI strategy across the organization

Connect with Dan:

LinkedIn: https://www.linkedin.com/in/dan-diasio/

Our links:

Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast

Follow us on YouTube: https://www.youtube.com/@InfoTechRG

This is not just a technology shift. It is a human, organizational, and identity transformation.

In this episode, we sit down with Ian Beacraft, Founder and Chief Futurist at Signal and Cipher, to talk about one of the most urgent questions facing leaders today: what happens to work, organizations, and identity in the age of AI?

Ian argues that the next two years will matter more than the last 30, and that AI is not just another tool. It is a platform reshaping economies, organizations, and how we define work itself.

We break down why most companies are getting AI wrong, the critical difference between culture and coordination, and how the rise of AI agents is shifting value from doing the work to designing it. We also cover what leaders need to do right now to stay ahead, including real world examples of failed AI adoption, the growing power of small teams, and the coming identity shift in the workplace.

Like and subscribe for weekly episodes.

In this video:

00:00 Intro

01:20 Biggest AI trends since last year

02:28 Why AI is not just a tool

03:28 AI, identity, and the redefinition of work

04:08 The real threat: Outdated organizational thinking

05:00 Culture vs coordination explained

07:08 The danger of replacing humans with AI

09:48 Employee anxiety & leadership impact

11:19 Why AI is NOT an IT problem

12:31 How organizations should approach AI

15:04 Encoding human expertise into AI systems

16:22 Trust, fear, and job replacement concerns

17:23 Leadership, vision & the social contract

20:50 Why most leaders lack vision today

21:46 “What you do in the next 2 years is your legacy”

23:14 Incremental vs transformational AI thinking

24:25 Encoding organizational identity for AI

29:02 Why everyone must redesign their own work

31:16 From doing work to designing work

34:50 How leaders should drive AI adoption

38:08 Lessons from Building an AI-native organization

41:23 Rethinking departments & organizational structure

42:33 AI agents running autonomous workflows

44:08 The future role of culture

45:12 Real examples of AI agents in action

48:21 Small teams vs large organizations

49:04 The rise of entrepreneurship with AI

50:07 Which jobs are most at risk

55:13 Finding your competitive moat in AI

56:47 Why AI adoption is Lagging

57:24 Prediction: The future will be messy

59:38 Why systems must break before they improve

01:00:29 The AI transformation is about people, not tech

Connect with Ian:

LinkedIn: https://www.linkedin.com/in/ianbeacraft

X: https://x.com/ianbcraft

Instagram: https://www.instagram.com/ianbcraft/

Our links:

Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast

Follow us on YouTube: https://www.youtube.com/@InfoTechRG

Are we giving up our freedom for convenience without realizing it?

In this episode, we sit down with Dr. Rumman Chowdhury, a globally recognized AI ethics leader featured in Time and Forbes, to unpack the real risks of artificial intelligence, Big Tech power, and data privacy.

As the former Head of AI Ethics at Twitter and Accenture, Dr. Chowdhury shares an insider perspective on how Big Tech is consolidating power, why narratives around AGI and “AI intelligence” are often misleading, and how everyday tools from apps to social media, are quietly shaping a surveillance-driven ecosystem.

This conversation dives into AI ethics, surveillance, and the future of work, and explores why trust in AI is declining even as adoption accelerates. We also break down the real-world implications of AI, and most importantly, how you can protect your data, reclaim your agency, and use AI more intentionally.

In this video:

00:00 Intro

01:16 What’s wrong with AI today

02:18 Why people trust AI less every year

03:09 Big tech vs the technology itself

04:22 Dangerous narratives about AI

06:09 Anthropomorphism and moral outsourcing

07:40 The myth of AGI and profit motives

09:20 The economics behind AI power

11:21 Consumer responsibility and the privacy paradox

13:42 “I have nothing to hide” explained

15:04 How big tech is consolidating control

16:42 What consumers should actually do

18:30 Real-world consequences of data misuse

21:05 From Pokémon Go to surveillance systems

22:29 The dilemma of social media and platforms

26:05 Can AI still be used for good

28:20 Algorithms, manipulation, and loss of agency

30:12 Inside AI ethics at Twitter

33:48 Why leadership and trust are changing

35:17 Surveillance capitalism and public backlash

37:31 How to think strategically about AI

41:19 Finding agency and intentional use of AI

45:06 Will society push back against AI power

52:02 The role of AI ethicists and builders

56:41 The future of work and automation reality

01:01:32 Why expertise and discernment matter most

01:06:35 Advice for business leaders using AI

01:11:33 Final thoughts on agency and discernment

Connect with Dr. Rumman Chowdhury:

LinkedIn: https://www.linkedin.com/in/rumman/

Instagram: https://www.instagram.com/rumman_c/?hl=en

Our links:

Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast

Follow us on YouTube: https://www.youtube.com/@InfoTechRG