AI Governance, Security & Accountability: What Should AI Be Allowed to Decide? | With Atul Rai

How much decision-making should we actually entrust to AI?

In this episode of the Regulating AI Podcast, recorded live at the Universal AI Awards launch in Delhi, Sanjay Puri speaks with Atul Rai, Co-founder & CEO of Staqu Technologies, about AI governance, accountability, security, AI models and the challenges of deploying artificial intelligence in mission-critical environments.

The conversation explores why AI governance cannot be an afterthought. As organizations deploy AI across sensitive areas, questions around data security, access, accountability, cost, reliability and human oversight become increasingly important.

Atul Rai discusses why the future of AI may not simply be about building larger and more powerful models, but about creating more efficient and optimized systems that can deliver meaningful outcomes while managing cost and complexity.

The conversation also looks at the use of AI in areas such as homeland security, public safety and crime detection. AI can identify patterns across enormous amounts of data and video that may be difficult for humans to process, but the question remains: when AI makes a prediction or recommendation, who should ultimately make the decision?

The discussion examines the limitations of current AI systems, including hallucinations, unpredictability and their difficulty in understanding consequences beyond the data they have been trained on.

Looking ahead, Atul Rai argues that the next generation of AI needs to go beyond prediction and move toward understanding consequences, while keeping human intention, ethics and accountability at the centre.

The episode ultimately asks a critical question for the AI era: If AI becomes increasingly powerful, how do we ensure that humans remain responsible for how that power is used?

Chapters:

00:00 – Why the future of AI isn’t just about bigger models

00:17 – Live from the Universal AI Awards in Delhi

01:03 – The risks of deploying AI faster than governance

01:30 – The real cost and ROI of implementing AI

01:54 – What happens when AI gets it wrong?

02:30 – AI decision-making and real-world consequences

02:46 – The growing challenge of AI data security

03:18 – Should AI information have different levels of access?

04:15 – How to choose AI use cases responsibly

04:32 – AI, homeland security and public safety

04:56 – Why human oversight matters in AI

05:28 – The challenge of AI costs and margins

05:59 – Why optimized AI models may matter more than bigger models

06:39 – Why AI governance requires a holistic approach

07:20 – Understanding the capabilities and limitations of AI

08:13 – Where should humans draw the line?

08:30 – How AI can connect patterns across crime data

09:21 – Why AI decisions need human monitoring

10:00 – Why today’s AI models still make mistakes

10:42 – What should we get right about AI today?

11:00 – Why today’s LLMs aren’t truly intelligent

11:40 – What should the AI of the future be able to predict?

12:20 – Bridging deterministic AI with a non-deterministic world

13:10 – The butterfly effect and AI’s limitations

13:33 – Can AI predict the next pandemic?

14:06 – Is AI good or bad? The role of human intention

14:14 – The responsibility behind AI’s power

14:36 – AI, medicine and solving difficult problems

14:44 – Closing thoughts

Guest: Atul Rai, Co-founder & CEO, Staqu Technologies

Host: Sanjay Puri

Podcast: Regulating AI

Recorded live: Universal AI Awards Launch, New Delhi

#AIGovernance #ArtificialIntelligence #ResponsibleAI #AIAccountability #AISecurity #AIRegulation #AIModels #HumanOversight #ComputerVision #FutureOfAI #AIIndia #StaquTechnologies #AtulRai #RegulatingAI #SanjayPuri