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Is Artificial Intelligence a Financial Liability?

AI’s that predict text and categorise images and speech look more like a liability than an asset



Artificial intelligence is a liability

Artificial Intelligence, meaning large foundational models that predict text and can categorize images and speech, looks more like a liability than an asset.

So far, the dollar damage has been minor. In 2019, a Tesla driver who was operating his vehicle with the assistance of the carmaker’s Autopilot software ran a red light and struck another vehicle. The occupants died and the Tesla motorist last week was ordered to pay $23,000 in restitution.

Tesla around the same time issued a recall of two million vehicles to revise its Autopilot software in response to a US National Highway Traffic Safety Administration’s (NHTSA) investigation that found the Autopilot’s safety controls lacking.

Twenty-three thousand dollars is not a lot for two lives, but the families involved are pursuing civil claims against the driver and against Tesla, so the cost may rise. And there are said to be at least a dozen lawsuits involving Autopilot in the US.

Meanwhile, in the healthcare industry, UnitedHealthcare is being sued because the nH Predict AI Model it acquired through its 2020 purchase of Navihealth has allegedly been denying necessary post-acute care to insured seniors.

Restraints required

Companies selling AI models and services clearly understand there’s a problem. They refer to “guardrails” put in place around foundational models to help them stay in their lane – even if these don’t work very well. Precautions of this sort would be unnecessary if these models didn’t contain child sexual abuse material and a panoply of other toxic content.

It’s as if AI developers read writer Alex Blechman’s viral post about tech companies interpreting the cautionary tale “Don’t Create the Torment Nexus” as a product roadmap and said, “Looks good to me.”

Of course there are older literary references that suit AI, such as Mary Shelley’s Frankenstein or Pandora’s Box – a particularly good fit given that AI models are frequently referred to as black boxes due to the lack of transparency about training material.

So far, the inscrutability of commercial models strewn with harmful content hasn’t taken too much of a toll on businesses. There’s a recent claim by Chris Bakke, founder and CEO at Laskie (acquired this year by a company calling itself X), that a GM chatbot used by a Watsonville, California, auto dealership was talked into agreeing to sell a 2024 Chevy Tahoe for $1 with a bit of prompt engineering. But the dealership isn’t likely to follow through on that commitment.

Still, the risk of relying on AI models is enough that Google, Microsoft, and Anthropic have offered to indemnify customers from copyright claims (which are numerous and largely unresolved). That’s not something you do unless there’s a chance of liability.


Authorities are still trying to figure out how AI liability should be assessed. Consider how the European Commission framed the issue as it works toward formulating a workable legal framework for artificial intelligence:

“Current liability rules, in particular national rules based on fault, are not adapted to handle compensation claims for harm caused by AI-enabled products/services,” the Commission said  last year. “Under such rules, victims need to prove a wrongful action/omission of a person that caused the damage. The specific characteristics of AI, including autonomy and opacity (the so-called ‘black box’ effect), make it difficult or prohibitively expensive to identify the liable person and prove the requirements for a successful liability claim.”

And US lawmakers have proposed a Bipartisan AI Framework to “ensure that AI companies can be held liable through oversight body enforcement and private rights of action when their models and systems breach privacy, violate civil rights, or otherwise cause cognizable harms.”

Don’t get too excited about seeing AI firm execs behind bars: The involvement of AI industry leaders in this process suggests any rules that emerge will be about as effective as other regulatory frameworks that have been defanged by lobbyists.

But excitement is part of the problem: There’s just so much hype about stochastic parrots, as AI models have been called.

AI models have real value in some contexts, as noted by security firm Socket, which has used ChatGPT to help flag software vulnerabilities. They’ve done wonders for speech recognition, translation, and image recognition, to the detriment of transcribers and CAPTCHA puzzles. They’ve reminded industry veterans of how much fun it was to play with Eliza, an early chatbot. They look like they have real utility in decision support jobs, provided there’s a human in the loop. And they’ve taken complex command line incantations, with their assorted flags and parameters, and turned them into equally complex text prompts that can go on for paragraphs.

But the automation enabled by AI comes at a cost. In a recent article for sci-fi trade magazine Locus, author and activist Cory Doctorow argued, “AI companies are implicitly betting that their customers will buy AI for highly consequential automation, fire workers, and cause physical, mental and economic harm to their own customers as a result, somehow escaping liability for these harms.”

Doctorow is sceptical that there’s a meaningful market for AI services in high-value businesses, due to the risks and believes we’re in an AI bubble. He points to GM Cruise as an example, noting that the self-driving car company’s business model – in limbo due to an pedestrian injury and recall – amounts to replacing each low-wage driver with 1.5 more costly remote supervisors, without precluding the possibility of accidents and associated lawsuits.


At least there’s some potential for low-value business associated with AI. These involve paying monthly to access an API for inaccurate chat, algorithmic image generation that co-opts artists’ styles without permission, or generating hundreds of fake news sites (or books) in a way that “floods the zone” with misinformation.

It seems unlikely that Arena Group’s claim that its AI platform can reduce the time required to create articles for publications like Sports Illustrated by 80-90 percent will improve reader satisfaction, brand loyalty, or content quality. But perhaps generating more articles than humanly possible across the firm’s hundreds of titles will lead to more page views by bots and more programmatic ad revenue from ad buyers too naïve to catch on.

Part of the problem is that the primary AI promoters – Amazon, Google, Nvidia, and Microsoft – operate cloud platforms or sell GPU hardware. They’re the pick-and-shovel vendors of the AI gold rush, who just want to sell their cloud services or number-crunching kit. They were all on-board for the blockchain express and cryptocurrency supremacy until that delusion died down.

They’re even more enthusiastic about helping companies run AI workloads, useful or otherwise. They’re simply cloud seeding, hoping to drive business to their rent-a-processor operations. Similarly, machine-learning startups without infrastructure are hoping that breathy talk of transformational technology will inflate their company valuation to reward early investors.

The AI craze can also be attributed in part to the tech industry’s perpetual effort to answer “What comes next?” during a time of prolonged stasis. Apple, Google, Amazon, Meta, Microsoft and Nvidia have all been doing their best to prevent meaningful competition and since the start of the cloud and mobile era in the mid-2000s, they’ve done so fairly well. Not that anti-competitive behaviour is anything new – recall the 2010 industry settlement with the US Department of Justice over the agreements between Adobe, Google, Intel, Intuit, and Pixar to avoid poaching talent from one another.

Microsoft made much of its AI integration with Bing, long overshadowed by Google Search, claiming it is “reinventing search.” But not much has changed since then – Bing reportedly has failed to take any market share from Google, at a time when there’s widespread sentiment that Google Search – also now larded with AI – has been getting worse.

Bring on 2024

To find out what comes next, we’ll have to wait for the Justice Department and regulators elsewhere in the world to force changes through antitrust enforcement and lawsuits. Because while Google has a lock on search distribution – through deals with Apple and others – and digital advertising – through its deal with Meta (cleared in the US, still under investigation in Europe and the UK) and other activities that piqued the interest of the Justice Department – neither the search business nor the ad business looks amenable to new challengers, no matter how much AI sauce gets added.

AI is a liability not just in the financial sense but also in the ethical sense. It promises wage savings – despite being extremely expensive in terms of training, development and environmental impact – while encouraging indifference to human labor, intellectual property, harmful output, and informational accuracy. AI invites companies to remove people from the equation when they often add value that isn’t obvious from a balance sheet.

There’s room for AI to be genuinely useful, but it needs to be deployed to help people rather than get rid of them. ®

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Artificial Intelligence

Lets Govern AI Rather Than Let It Govern Us




A pivotal moment has unfolded at the United Nations General Assembly. For the first time, a resolution was adopted focused on ensuring Artificial Intelligence (AI) systems are “safe, secure and trustworthy”, marking a significant step towards integrating AI with sustainable development globally. This initiative, led by the United States and supported by an impressive cohort of over 120 other Member States, underscores a collective commitment to navigating the AI landscape with the utmost respect for human rights.

But why does this matter to us, the everyday folks? AI isn’t just about robots from sci-fi movies anymore; it’s here, deeply embedded in our daily lives. From the recommendations on what to watch next on Netflix to the virtual assistant in your smartphone, AI’s influence is undeniable. Yet, as much as it simplifies tasks, the rapid evolution of AI also brings forth a myriad of concerns – privacy issues, ethical dilemmas and the very fabric of our job market being reshaped.

The Unanimous Call for Responsible AI Governance

The resolution highlights a crucial understanding: the rights we hold dear offline must also be protected in the digital realm, throughout the lifecycle of AI systems. It’s a call to action for not just countries but companies, civil societies, researchers, and media outlets to develop and support governance frameworks that ensure the safe and trustworthy use of AI. It acknowledges the varying levels of technological development across the globe and stresses the importance of supporting developing countries to close the digital divide and bolster digital literacy.

The United States Ambassador to the UN, Linda Thomas-Greenfield, shed light on the inclusive dialogue that led to this resolution. It’s seen as a blueprint for future discussions on the challenges AI poses, be it in maintaining peace, security, or responsible military use. This resolution isn’t about stifling innovation; rather, it’s about ensuring that as we advance, we do so with humanity, dignity, and a steadfast commitment to human rights at the forefront.

This unprecedented move by the UN General Assembly is not just a diplomatic achievement; it’s a global acknowledgment that while AI has the potential to transform our world for the better, its governance cannot be taken lightly. The resolution, co-sponsored by countries including China, represents a united front in the face of AI’s rapid advancement and its profound implications.

Bridging the Global Digital Divide

As we stand at this crossroads, the message is clear: the journey of AI is one we must steer with care, ensuring it aligns with our shared values and aspirations. The resolution champions a future where AI serves as a force for good, propelling us towards the Sustainable Development Goals, from eradicating poverty to ensuring quality education for all.


The emphasis on cooperation, especially in aiding developing nations to harness AI, underscores a vision of a world where technological advancement doesn’t widen the gap between nations but brings us closer to achieving global equity. It’s a reminder that in the age of AI, our collective wisdom, empathy, and collaboration are our most valuable assets.

Ambassador Thomas-Greenfield’s remarks resonate with a fundamental truth: the fabric of our future is being woven with threads of artificial intelligence. It’s imperative that we, the global community, hold the loom. The adoption of this resolution is not the end, but a beginning—a stepping stone towards a comprehensive framework where AI enriches lives without compromising our moral compass.

At the heart of this resolution is the conviction that AI, though devoid of consciousness, must operate within the boundaries of our collective human conscience. The call for AI systems that respect human rights isn’t just regulatory rhetoric; it’s an appeal for empathy in algorithms, a plea to encode our digital evolution with the essence of what it means to be human.

This brings to light a pertinent question: How do we ensure that AI’s trajectory remains aligned with human welfare? The resolution’s advocacy for cooperation among nations, especially in supporting developing countries, is pivotal. It acknowledges that the AI divide is not just a matter of technological access but also of ensuring that all nations have a voice in shaping AI’s ethical landscape. By fostering an environment where technology serves humanity universally, we inch closer to a world where AI’s potential is not a privilege but a shared global heritage.

Furthermore, the resolution’s emphasis on bridging the digital divide is a clarion call for inclusivity in the digital age. It’s a recognition that the future we craft with AI should be accessible to all, echoing through classrooms in remote villages and boardrooms in bustling cities alike. The initiative to equip developing nations with AI tools and knowledge is not just an act of technological philanthropy; it’s an investment in a collective future where progress is measured not by the advancements we achieve but by the lives we uplift.

Uniting for a Future Shaped by Human Values

The global consensus on this resolution, with nations like the United States and China leading the charge, signals a watershed moment in international diplomacy. It showcases a rare unity in the quest to harness AI’s potential responsibly, amidst a world often divided by digital disparities. The resolution’s journey, from conception to unanimous adoption, reflects a world waking up to the reality that in the age of AI, our greatest strength lies in our unity.

As we stand at the dawn of this new era, the resolution serves as both a compass and a beacon; a guide to navigate the uncharted waters of AI governance and a light illuminating the path to a future where technology and humanity converge in harmony. The unanimous adoption of this resolution is not just a victory for diplomacy; it’s a promise of hope, a pledge that in the symphony of our future, technology will amplify, not overshadow, the human spirit.

In conclusion, “Let’s Govern AI Rather Than Let It Govern Us” is more than a motto; it’s a mandate for the modern world. It’s a call to action for every one of us to participate in shaping a future where AI tools are wielded with wisdom, wielded to weave a tapestry of progress that reflects our highest aspirations and deepest values.

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Artificial Intelligence

KASBA.AI Now Available on ChatGPT Store

ChatGPT Store by OpenAI is the new platform for developers to create and share unique AI models with monetization opportunities



chatgpt store

OpenAI, the leading Artificial Intelligence research laboratory has taken a significant step forward with the launch of the ChatGPT Store. This new platform allows developers to create and share their unique AI models, expanding the capabilities of the already impressive ChatGPT. Among the exciting additions to the store are Canva, Veed, Alltrails and now KASBA.AI with many more entering every day.

About OpenAI

OpenAI, founded by Elon Musk and Sam Altman, has always been at the forefront of AI research. With a mission to ensure that artificial general intelligence benefits all of humanity, they have consistently pushed the boundaries of what is possible in the field.

OpenAI’s ChatGPT has already changed the way we interact with technology with its ability to generate coherent and contextually relevant responses. Now, with the ChatGPT Store, OpenAI is aiming to empower developers and non technical users to contribute and build upon this powerful platform. chatgpt store

What is the ChatGPT Store?

The ChatGPT Store is an exciting initiative that allows developers to create, share and in time monetise their unique AI models. It serves as a marketplace for AI models that can be integrated with ChatGPT.

This means that users can now have access to a wide range of specialised conversational AI models, catering to their specific needs. The ChatGPT Store opens up a world of possibilities, making AI more accessible and customisable than ever before.

chatgpt store

Key Features of the ChatGPT Store

Some unique features of the store include customisable AI models, pre trained models for quick integration and the ability for developers to earn money by selling their models.

Developers can also leverage the rich ecosystem of tools and resources provided by OpenAI to enhance their models. This collaborative marketplace fosters innovation and encourages the development of conversational AI that can cater to various industries and use cases.

Impact on Industries and Society

The launch of the ChatGPT Store has far reaching implications for industries and society as a whole. By making AI models more accessible and customisable, businesses can now leverage conversational AI to enhance customer support, automate repetitive tasks and improve overall efficiency.

From healthcare and finance to education and entertainment the impact of AI on various sectors will only grow with the availability of specialised models on the ChatGPT Store. This democratisation of conversational AI technology will undoubtedly pave the way for a more connected and efficient world.

Ethical Considerations

As with any technological advancement, ethical considerations are crucial. OpenAI places a strong emphasis on responsible AI development and encourages developers to adhere to guidelines and principles that prioritize user safety and privacy. The ChatGPT Store ensures that AI models are vetted and reviewed to maintain high standards.

OpenAI is committed to continuously improving the user experience, and user feedback plays a vital role in shaping the future of AI development. For specific concerns regarding AI and data protection visit Data Protection Officer on ChatGPT Store.

dpo chatgpt store

KASBA.AI on ChatGPT Store

One of the most exciting additions to the ChatGPT Store is KASBA.AI, your guide to the latest AI tool reviews, news, AI governance and learning resources. From answering questions to providing recommendations, KASBA.AI hopes to deliver accurate and contextually relevant responses. Its advanced algorithms and state of the art natural language processing make it a valuable asset to anyone looking for AI productivity tools in the marketplace.


OpenAI’s ChatGPT Store represents an exciting leap forward in the world of conversational AI. With customisable models, the ChatGPT Store empowers developers to create AI that caters to specific needs, with the potential to propel industries and society to new horizons..

OpenAI’s commitment to responsible AI development should ensure that user safety and privacy are prioritised; lets keep an eye here! Meanwhile as we traverse this new era of conversational AI, ChatGPT Store will undoubtedly shape the future of how we interact with technology in time to come with potentially infinite possibilities.

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Artificial Intelligence

Two AIs Get Chatty: A Big Leap at UNIGE



two ais get chatty

Chatting AIs: How It All Started

Scientists at the University of Geneva (UNIGE) have done something super cool. They’ve made an AI that can learn stuff just by hearing it and then can pass on what it’s learned to another AI. It’s like teaching your friend how to do something just by talking to them. This is a big deal because it’s kind of like how we, humans, learn and share stuff with each other, but now machines are doing it too!

Two AIs Get Chatty By Taking Cues from Our Brains

This whole idea came from looking at how our brains work. Our brains have these things called neurons that talk to each other with electrical signals, and that’s how we learn and remember things. The UNIGE team made something similar for computers, called artificial neural networks. These networks help computers understand and use human language, which is pretty awesome.

How Do AIs Talk to Each Other?

For a long time, getting computers to learn new things just from words and then teach those things to other computers was super hard. It’s easy for us humans to learn something new, figure it out, and then explain it to someone else. But for computers? Not so much. That’s why what the UNIGE team did is such a big step forward. They’ve made it possible for one AI to learn a task and then explain it to another AI, all through chatting.

two ais get chatty cool

Learning Like Us

The secret here is called Natural Language Processing (NLP). NLP is all about helping computers understand human talk or text. This is what lets AIs get what we’re saying and then do something with that info. The UNIGE team used NLP to teach their AI how to understand instructions and then act on them. But the real magic is that after learning something new, this AI can turn around and teach it to another AI, just like how you might teach your friend a new trick.

Breaking New Ground in AI Learning

The UNIGE team didn’t just stop at making an AI that learns from chatting. They took it a step further. After one AI learns a task, it can explain how to do that task to another AI. Imagine you figured out how to solve a puzzle and then told your friend how to do it too. That’s what these AIs are doing, but until now, this was super hard to achieve with machines.

From Learning to Teaching

The team started with a really smart AI that already knew a lot about language. They hooked it up to a simpler AI, kind of like giving it a buddy to chat with. First, they taught the AI to understand language, like training it to know what we mean when we talk. Then, they moved on to getting the AI to do stuff based on what it learned from words alone. But here’s the kicker: after learning something new, this AI could explain it to its buddy AI in a way that the second one could get it and do the task too.

A Simple Task, A Complex Achievement

The tasks themselves might seem simple, like identifying which side a light was flashing on. But it’s not just about the task; it’s about understanding and teaching it, which is huge for AI. This was the first time two AIs communicated purely through language to share knowledge. It’s like if one robot could teach another robot how to dance just by talking about it. Pretty amazing, right?

Why This Matters

This is a big deal for the future. It’s not just about AIs chatting for fun; it’s about what this means for robots and technology down the line. Imagine robots that can learn tasks just by listening to us and then teach other robots how to do those tasks. It could change how we use robots in homes, hospitals, or even in space. Instead of programming every single step, we could just tell them what we need, and they’d figure it out and help each other out too. It’s like having a team of robots that learn from each other and us, making them way more useful and flexible.

The UNIGE team is already thinking about what’s next. Their AI network is still pretty small, but they believe they can make it bigger and better. We’re talking about robots that not only understand and learn from us but also from each other. This could lead to robots that are more like partners, helping solve problems, invent new things, and maybe even explore the universe with us.

What’s the Future?

This adventure isn’t just about what’s happening now. It’s about opening the door to a future where robots really get us, and each other. The UNIGE team’s work is super exciting for anyone who’s into robots. It’s all about making it possible for machines to have chats with each other, which is a big deal for making smarter, more helpful robots.

The brains behind this project say they’ve just started. They’ve got a small network of AI brains talking, but they’re dreaming big. They’re thinking about making even bigger and smarter networks. Imagine humanoid robots that don’t just understand what you’re telling them but can also share secrets with each other in their own robot language. The researchers are pretty stoked because there’s nothing stopping them from turning this dream into reality.

So, we’re looking at a future where robots could be our buddies, understanding not just what we say but also how we say it. They could help out more around the house, be there for us when we need someone to talk to, or even work alongside us, learning new things and teaching each other without us having to spell it all out. It’s like having a robot friend who’s always there to learn, help, and maybe even make us laugh.

Wrap up

What started as a project at UNIGE could end up changing how we all live, work, and explore. It’s a glimpse into a future where AIs and robots are more than just tools; they’re part of our team, learning and growing with us. Who knows what amazing things they’ll teach us in return?

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