Responsible AI and AI-related issues - What are your views?

Sat, 1 Feb 2025 19:56:33 GMT

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AI is evolving at an unprecedented pace, transforming industries and reshaping how we interact with technology. But with great power comes great responsibility. This forum is dedicated to Responsible AI and AI Agents, tackling crucial topics like AI governance, ethical AI frameworks, regulatory shifts, and the role of autonomous agents in business and society.

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What excites you about Responsible AI?
What challenges do you foresee in governing AI agents?
What’s one AI-related issue keeping you up at night?

Let’s build a responsible AI future—together. 🚀

Tue, 4 Feb 2025 05:42:24 GMT

I strongly believe in one thing.

If you become overly creative to create a solution where no problem exists, you will unfold a pandora box of unprecedented problems.
So the fundamental responsibility of creating any technology lies in asking oneself the questions,

Am I doing this due to over enthusiasm or to get a larger piece of profit cake?
Is it viable for human well being?
What problem is it solving?
What kind of problem will it create in the next 50 years?
Do I have a mitigation plan for those problems?

If we ask the same questions to AI, which we already are neck deep, there are many challenges that surface, from weaker sex exploitation, child abuse, fakery, confusion, making artists redundant etc... If you look at CIVITAI on Image and Video generation, you will know major part of what I am speaking. This AI looks like more of a Man's fantasy than real problem solution.

Nevertheless, I am going to be a part of solution, not the problem itself. Problem has been created already!
1. Before giving away AI to every tom dick and harry, make a policy or protocol, who can use it
2. Throwing marijuana into public, and asking them to be responsible consumers is more than foolishness
3. Every step we put forward in this domain must include Thinkers, Leaders, Community Heads to understand how it would adversely affect the delicate social and traditional thread.

If we don't do this now, our children will regret our intelligence. At this juncture Sense is more important than Science

Wed, 5 Feb 2025 02:27:45 GMT

What excites you about Responsible AI : Share accountability between man and machine.
What challenges do you foresee in governing AI agents : NOT having a global Consensus.
What’s one AI-related issue keeping you up at night : It Mae kill creativity of young generation.

Wed, 5 Feb 2025 11:53:35 GMT

First stage, augmentation, when engineers get suggestions on actions, next stage authorise AI to take action. Question is, how much power are you willing to give to AI? What will be the legal consequences? Advantages will be immense though. The number of times I need to wait for a human to understand my complex problem and then get cut off, or they go on holiday half way through resolving the issue. I'd love to see companies with non-life critical systems lead the way. I had a complex issue with a photo printing app not that long ago. The customer service seemed to be lightening quick and was able to understand complex matters and pick apart the problem. I was left wondering if it was AI or not. The speed of response suggested to me that it was. The more we can rely on chat based support the better. I can hold 50 conversations at once via chat platforms (as long as they don't time-out for no particular reason beyond trying to alter the performance stats), I can only hold one convo over the phone (or none if I am left on hold), drives me insane. There is a HUGE productivity gain to be made just from that. Would be nice if that chat bots advertised what underlying platform they are using so customers can see how intelligent the chat bots are. 99% are still are annoying as hell.

Wed, 5 Feb 2025 12:02:04 GMT

Everything seems ok on the happy path. Its when things go wrong or take unexpected outcomes due to use of AI, is when the real conundrum kicks in. Who will be deemed responsible for unexpected outcomes - end user, deployers of AI systems or AI providers? A correlated example would be autonomous driving vehicles, users behind the wheels are responsible or the car manufacturers? I think answer would lie somewhere in the middle and direction to take would be shared responsibility model with clearly defined responsibilities for each parties involved.

Realize Artificial Intelligence with an Actual Business Use Case

Wed, 5 Feb 2025 12:12:25 GMT

A Business Use Case simply suggesting they want to use AI in an XYZ Workflow is not a Use Case but merely a desperation under Competitive Pressure. It's more of a desire than a need.

Artificial Intelligence has got a huge Potential, if planned as part of a Rhobust Framework. The basic Problem with AI is basically how Organisations are pursuing it. Mostly as an association or application directly in the Implementation without much Governance/Discovery Directions which makes it prone to Failures (I hate the Word but that's exactly how it is). With the Hype of Artificial Intelligence, it has already set the Standards high and a lot of unrealistic Expectations. The Innovations/Projections/Expectations around AI are usually happening within secluded Teams across the Global Organisations. This is definitely scary in the long run, one may unlock a Super AI Prototype by virtue of the Experimentation.

As autonomous as a Decentralized process sounds, a Governed Centralized body can really help maintain/approve/rate multiple Initiatives across the Globe. There are multiple factors on how such a body be Governed from faceting Organisations to budgeting requirements but there is a necessity to for an overall Governance.

This would be dream setup with a major Challenge on how to deal with monopoly of this Centralized Organisation and there are no of ways, but in the end it' break into various Organisations offering its own Set of Services.

What should be the Pre-Requisites to even engage for the conversation to establish for an AI Landscape in a Transformation Initiative (hope Digital) ?
✅ Understand to adhere to the Specific Organisation/Region/State/Country/Global Data Regulations & Guidelines
✅ Understand and mitigate for Data Residency & Security
✅ Identification of the inconsistencies in existing Data
✅ Data Validations and Correction Approach
✅ Data Procedures to handle for the autonomous Validations

Definitely not a Complete list and I can literally Go On for Hours. Ironically there is no Argument to the fact that while Data is the fuel to AI & Testing is it's Validation, still these are the most underestimated and ignored domains in an AI Realm.

Hoping for things to get better with realization and acceptance of Actual AI Use Cases !!!

Any Skill/Capability in the Corporate World is for a Business Use Case, while readiness should be the plan, it needs to be measurable with a defined Business ROI

Mon, 10 Feb 2025 20:21:31 GMT

Here are my thoughts on the topics :
What Excites Me About Responsible AI?
Ethical Alignment: The potential for AI to align with human values and ethical principles is incredibly exciting. Responsible AI practices ensure that AI systems are developed and deployed in ways that respect human rights, minimize bias, and promote fairness. This alignment fosters trust and acceptance among users and stakeholders, paving the way for widespread adoption.
Transparency: Transparency in AI governance is foundational to building trust, ensuring accountability, and fostering a culture of ethical technology use. It involves revealing complex processes in an accessible manner, allowing stakeholders to understand, assess, and hold AI systems accountable.
Challenges in Governing AI Agents :
Bias and Fairness: AI agents can inadvertently perpetuate or amplify existing biases if not carefully managed. The case study of a financial services company addressing biased outcomes in its AI-driven credit scoring system exemplifies the importance of proactive bias mitigation.
AI-Related Issue Keeping Me Up at Night
Data Integrity and Privacy: The routine deletion of critical employee data, as observed in some organizations, raises significant concerns about data integrity and privacy. This practice not only deprives individuals of proof of compliance but also exposes organizations to legal and reputational risks. Ensuring robust data governance frameworks that protect employee data while maintaining transparency is a pressing issue. I have personally experienced this issue.

Thu, 13 Feb 2025 14:47:15 GMT

Responsible AI is exciting because it holds the potential to shape a future where technology aligns with human values, ethics, and fairness. It offers a path to ensure that AI serves all people equitably, prioritizes transparency, and is accountable for its outcomes. It’s thrilling to think about a world where AI amplifies human potential without causing harm, reinforcing societal good, and encouraging collaboration.

As for challenges in governing AI agents, one of the most pressing is ensuring accountability in decision-making. AI systems can make complex decisions, but when they go wrong, pinpointing where the fault lies—whether with the algorithm, data, or human oversight—can be difficult. Furthermore, regulatory bodies will need to adapt quickly to the rapid pace of AI advancements while keeping up with ethical standards, privacy concerns, and the risk of misuse.

A concern that often keeps me up at night is the potential for biased or unfair outcomes in AI systems. AI models learn from historical data, and if that data reflects existing prejudices, it can perpetuate or even amplify them. Ensuring that AI is not reinforcing harmful stereotypes or leaving out marginalized communities is a significant challenge, and tackling that issue is crucial to making AI truly fair and inclusive.

Tue, 4 Mar 2025 17:55:12 GMT

I find the conversation about AI’s evolving role and the power we grant it fascinating. In many scenarios, the first stage is augmentation—where AI simply suggests actions to human operators. It’s like having a smart assistant that flags the key issues and guides you toward a decision. But the second stage—actually authorizing AI to take action—raises a host of questions around accountability and liability.

How much power are we willing to give AI?
For some non–life-critical systems, there is a real opportunity to let AI handle complex tasks faster and more efficiently than human agents. Take the example of customer service in a photo-printing app: if I have a nuanced, detailed question and need an immediate response, an AI capable of processing my query almost instantly is a huge plus. It can also handle multiple conversations at once, which completely outstrips what a single human agent can do by phone. This means less waiting on hold, fewer cutoffs or holiday-related handovers, and more consistency. Clearly, that productivity gain is a big deal.

On the flip side, what are the legal implications?
If an AI system acts independently—whether it’s handling refunds, making changes to a service, or even diagnosing and solving complex errors—who is responsible when it gets something wrong? In some industries, an AI mistake is just a minor inconvenience, but in others, it could have serious repercussions. We’ll need robust frameworks for liability and accountability: should the company deploying the AI bear the responsibility, or do we look at the developers who trained it?

A call for transparency and standards
It would be helpful if chatbots disclosed the AI platform behind them, so users know when they’re talking to an advanced system and can gauge how “intelligent” or reliable it might be. Right now, most chatbots still feel frustratingly limited. But as they improve, we should push for clear disclosure about when AI is involved—and to what extent—so people can judge how much to trust it.

In the end, I’d love to see companies with lower-risk services take the lead on deploying AI-driven support. Let them refine the processes and demonstrate real-world results before these systems make their way into higher-stakes applications. We get the benefits of quicker, more thorough support while ironing out accountability and legal frameworks. AI is clearly on a path to handle more tasks in our daily lives; we should shape that path carefully, reaping the efficiency gains while staying vigilant about oversight and consequences.

Tue, 4 Mar 2025 17:56:53 GMT

Thank you for your replies S.Narayan, V.Pidikiti, V.Gulati, S.Lewry, T.Mittal, H. Thawait, V. Sridhara.
Let us keep the conversation going.