Good morning. In this second part of our special edition series, we’re breaking down the dark side of artificial intelligence, the moral and ethical challenges and questions posed by the increasing proliferation of the technology. 

The issues, as always, are manifold.

Relatedly, check out the latest episode of our podcast, an interview with Pindrop about battling audio deepfakes.

— Ian Krietzberg, Editor-in-Chief, The Deep View

The ethics of AI

At the beginning of 2024, the ethics of generative artificial intelligence came into focus in a major way, centered in a dark spotlight around Taylor Swift; a series of sexually explicit, AI-generated deepfakes of the singer went viral on social media, leading to a weeks-long period in late January and early February where it became hard to avoid a positive flood of explicit, AI-generated photos of a number of female celebrities. 

Eventually, accounts were banned and the photos were removed, but the problem didn’t go away. 

Deepfake harassment: This kind of deepfake harassment wasn’t a new phenomenon; it’s been going on since at least 2017. But, back in that pre-GenAI era, it took bad actors hours or even days to produce just one deepfake image; and even then, it wasn’t all too convincing. 

According to recent research from the nonprofit Internet Matters, some 13% of teenagers say they have had experience with explicit deepfake image abuse. 

A look back at related stories we’ve done in the past year: 

In the U.S., there remains no federal legislation regarding this kind of deepfake abuse. The Defiance Act, which would allow victims to sue over the spread of nonconsensual explicit deepfakes, passed the Senate over the summer, but has yet to pass the House. Legislation regarding the matter remains patchwork at best in the states; and while the policymakers debate regulatory approaches, the problem persists, with dozens of websites specifically marketed as AI-powered ‘nudify’ tools remaining operational.

The city of San Francisco in August filed suit against 16 of those websites. 

The wider impacts

But the ethical impacts of deepfakes stretch far beyond image abuse and into weaponized identity hijacking that has enabled the spread of a truly concerning variety of misinformation. 

It’s not just election-related information; AI-generated books, images and articles have spread across the internet, threatening widespread information pollution that has already had dangerous impacts. 

In August, we wrote about a British family who was poisoned after using what turned out to be an AI-generated mushroom hunting guidebook; in the process, I discovered several AI-generated mushroom guidebooks listed on Amazon, which the company removed following my request for comment. 

And, pivoting away from the deepfake side of things, issues of generative AI leading to mass surveillance and algorithmic discrimination have proliferated: a November investigation uncovered discrimination baked into Denmark’s digitized social welfare program; the steady adoption of AI into already discriminatory predictive policing efforts has continued; and the adoption of generative AI by hospitals has continued, leading to many concerned nurses and patients alike. 

A look back at related stories we’ve done in the past year: 

The psychological, sociological impacts of AI companionship, meanwhile, came into sharp focus when a boy died by suicide after falling in love with a Character AI chatbot. To date, a second lawsuit has been filed against the company by the mother of a teenage boy who, she argues, became mentally ill and unstable due to a close relationship with bots on Character.

And the environmental impacts of increasing investments in generative AI, meanwhile, have steadily pushed much of the Big Tech sector further from achieving their climate goals, with the bulk of these giants — Meta, Google, Microsoft and Amazon — pursuing nuclear power specifically to meet their AI energy requirements. But, before the nuclear comes online, AI data centers are taking advantage of fossil fuels, a situation that is leading to spiking emissions and a burgeoning public health crisis due to steadily worsening air quality.

There’s also the general cybersecurity war that’s been taking place, with cybercriminals vastly empowered by generative AI tools, which have introduced specificity, speed and scale to their operations. Cybersecurity officials have, meanwhile, adopted generative AI tools to fight back against ever-increasing attacks, even as others work to educate companies and individuals about the myriad security risks posed by AI, with AI and because of AI. 

On top of all this, there are ongoing legal battles regarding the legality of training generative AI models on copyrighted material, even as those models are beginning to be used to replace human workers, a challenging dynamic for the job market going forward. 

In sum, 2024 was a busy year of AI proliferation and integration, and the resulting moral and ethical impacts are vast, to say the least. 

The experts I spoke to expect 2025 to be worse. 

Looking ahead: Nell Watson, an author and leading AI ethicist, told me that, with the rise of the increasingly autonomous agentic AI that we talked about yesterday, “ordinary members of the public will be tasked with teaching and managing these systems, something that remains a major, uncertain challenge even for experts.”

Ajay Amlani, president of iProov, expects deepfake fraud specifically to become fully weaponized in 2025: “a wave of account takeovers and fraudulent transactions will force banking regulators worldwide to take decisive action. Led by pioneers like Thailand and Vietnam, countries will mandate the implementation of biometric verification for payment authentication,” he said. 

Amlani added that he expects a “deepfake of a Fortune 500 CEO will cause significant disruption in the financial markets.” 

Typeform CPO Aleks Bass said that people will “get scammed at a higher rate than what we are seeing now. 

A look back at related stories we’ve done in the past year: 

Cybersecurity firm Exabeam expects, similar to much of what we’ve already discussed, highly enhanced and empowered cybercriminals, leading to new types of attacks and increasing exploitation. 

Steve Povolny, one of Exabeam’s co-founders, said that, in 2025, “AI will democratize malware creation.”

Povolny thinks that video-based deepfakes will soon become “imperceptible from reality,” unleashing a “devastating new wave of social engineering attacks” that will allow “criminals to impersonate executives, forge high-stakes transactions, and extract massive payouts from unsuspecting victims. With AI making deepfakes accessible at the push of a button, the potential for financial fraud will explode, forcing organizations to rethink how they verify identity in an increasingly deceptive world.”

Harry Muncey, Senior Director of Data Science, and Responsible AI at Elsevier, expects the adoption of generative AI to continue, leading to improved confidence in “low-risk use cases” that “will lead to pressure for innovation and use in higher-risk environments, such as healthcare, where the need for robust guardrails is clearly critical.”

And Vijay Balasubramaniyan, the co-founder of CEO of Pindrop, expects deepfake attacks to “accelerate at an alarming rate” next year. 

I wholeheartedly expect — and I really hope I am wrong — that the ethical challenges related to artificial intelligence will become much more significant throughout 2025 as adoption continues, legislation lags and systems become more capable. 

A year ago, I saw no clear solution to the problem of deepfake abuse and harassment; I think we have made no progress on that front whatsoever. Instances will continue to occur at small and large scales. People will get hurt. And while I do worry about misinformation and its spread online, I am far more concerned about schools and this new, dangerous form of bullying and harassment that, without governance, oversight and regulation, will continue unabated. 

I also expect addictions to and obsessions with anthropomorphized GenAI chatbots to steadily spike as vulnerable people interact with these systems, leading to a heavy, noticeable increase in digital isolation, something that may start to become more clearly associated with mental health struggles. 

I expect we will additionally begin to see the problems of overreliance, specifically in high-risk environments. Hospitals, I think, will run into at least a few well-publicized instances regarding generative AI misuse.

As with any problem, things have to get worse before they get better — I think 2025 will be the year that these issues move off the fringe to become more mainstream; only then might action be taken against them. I do not expect that action to come soon, however. 

On the copyright front, I think we’ll see some significant movement from the big copyright infringement cases this year (Authors Guild and New York Times) that may — and that’s a very big ‘may’ — have implications for the future development of foundation models. I don’t expect mass job loss anytime soon — or at all, really — but I do think we’ll start to see a reduction in hiring due to internal reliance on AI tools. 

On the environmental front, the optimist in me hopes that the sheer cost of data center operation will drive massive innovations in energy efficiency, which will have positive impacts on sustainability. This, however, might very well be wishful thinking; the complexity and use of generative AI systems continues to grow, meaning energy efficiencies will simply free developers up to handle bigger workloads, rather than reducing their energy use. 

My areas of biggest concern involve algorithmic surveillance and discrimination, unsustainability, deepfake abuse and artificial companionship; as these issues continue to worsen — I expect them all to become hallmarks of this next year — global society will be pushed to the edge of truly radical transformation. 

🤔 Your thought process:

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