Two 2025 publications, "AI 2027" (Kokotajlo et al., 2025) and "If Anyone Builds It, Everyone Dies" (Yudkowsky & Soares, 2025), assert that superintelligent artificial intelligence will almost certainly destroy or render humanity obsolete within the next decade. Both rest on the classic chain formulated by Good (1965) and Bostrom (2014): intelligence explosion, superintelligence, lethal misalignment. This article subjects each link to the empirical record of 2023-2025. Sixty years after Good's speculation, none of the required phenomena (sustained recursive self-improvement, autonomous strategic awareness, or intractable lethal misalignment) have been observed. Current generative models remain narrow, statistically trained artefacts: powerful, opaque, and imperfect, but devoid of the properties that would make the catastrophic scenarios plausible. Following Whittaker (2025a, 2025b, 2025c) and Zuboff (2019, 2025), we argue that the existential-risk thesis functions primarily as an ideological distraction from the ongoing consolidation of surveillance capitalism and extreme concentration of computational power. The thesis is further inflated by the 2025 AI speculative bubble, where trillions in investments in rapidly depreciating "digital lettuce" hardware (McWilliams, 2025) mask lagging revenues and jobless growth rather than heralding superintelligence. The thesis remains, in November 2025, a speculative hypothesis amplified by a speculative financial bubble rather than a demonstrated probability.

Rumman Chowdhury often has trouble sleeping, but, to her, this is not a problem that requires solving. She has what she calls "2am brain", a different sort of brain from her day-to-day brain, and the one she relies on for especially urgent or difficult problems. Ideas, even small-scale ones, require care and attention, she says, along with a kind of alchemic intuition. "It's just like baking," she says. "You can't force it, you can't turn the temperature up, you can't make it go faster. It will take however long it takes. And when it's done baking, it will present itself."

The age of AI is upon us, changing our lives in ways we could never have imagined. Through emerging advances in AI technology, we are seeing an array of new applications that are transforming industries and improving our daily routines. As AI and digital technologies based on big data become increasingly sophisticated and are used to bring significant improvements in service quality and productivity, it is crucial to consider the ethical implications of these technologies. For instance, AI systems that make autonomous decisions about individuals, such as loan acceptance or insurance policies, can produce biased outcomes if the algorithms used to train the AI are not designed to be fair and unbiased. This can lead to situations where AI systems make unethical or unfair decisions without anyone being able to intervene. Further ethical issues raised include coercion of data disclosure, dehumanization and threat to human dignity, social deprivation, disempowerment, and social engineering.

And so the risk here is not that the AI is truly sentient but that we are well-poised to create sophisticated machines that can imitate humans to such a degree that we cannot help but anthropomorphize them--and that large tech companies can exploit this in deeply unethical ways. As should be clear from the way we treat our pets, or how we've interacted with Tamagotchi, or how we video gamers reload a save if we accidentally make an NPC cry, we are actually very capable of empathizing with the nonhuman. Systems engineer and historian Lilly Ryan warns that what she calls ecto-metadata--the metadata you leave behind online that illustrates how you think--is vulnerable to exploitation in the near future. In her section of the work, Suzanne Kite draws on Lakota ontologies to argue that it is essential to recognize that sapience does not define the boundaries of who (or what) is a "being" worthy of respect. This is the AI ethical dilemma that stands before us: the need to make kin of our machines weighed against the myriad ways this can and will be weaponized against us in the next phase of surveillance capitalism.

A European digital public sphere has to be engineered--but that doesn't mean pursuing an AI dystopia or creating a European Facebook. In the early 20th century Simone Weil wrote: 'Imaginary evil is romantic and varied; real evil is gloomy, monotonous, barren, boring. Imaginary good is boring; real good is always new, marvellous, intoxicating.' Fascinated by the romantic and varied evils presumably awaiting humanity in the face of Ray Kurzweil's artificial-intelligence'singularity', many institutions and expert groups around the world proceeded to draw up lists of values to be respected, no matter how dystopic our transhumanistic future would be. A few prominent examples are the Organisation for Economic Co-operation and Development and the European Commission, with its high-level expert group on AI. Important value principles were endorsed for future AI systems, such as human oversight, safety, privacy, transparency, fairness and wellbeing.

A team of researchers at Cornell Tech, Cornell University's tech-focused research campus, has developed a forecast for how technologies like artificial intelligence could shape cities in the coming decade. After a year of work, the team released its first "Horizon Scan" report last week to discuss the potential risks and applications of recent advancements in urban tech. The forecast report predicts areas where the most radical and rapid changes in urban tech could take place, touching on topics such as "supercharged" smart city infrastructure, the use of sustainable building materials and machine learning in the public sector, among other areas of interest. The project was led by Anthony Townsend, urbanist in residence at the Jacobs Urban Tech Hub at Cornell Tech, who has spent years studying tech-related issues like the digital divide. He said the goal of the Horizon Scan was to create a road map "to make better decisions about applied research" in urban tech. Townsend said the need to weigh potential pros and cons of machine learning's applications in the public sector is a recurring factor in the report.

So the other day, I was having a somewhat politically incorrect conversation with my fiancé. At one point, I slightly rebuked her by saying, "Honey, you know, Mark Zuckerburg could be listening to us as we speak!" Yeah, we've grown quite comfortable with Big Brother in our household. In line with that, I wanted to talk today a little bit about what's been called Surveillance Capitalism. Lately, I've been commenting a lot on artificial intelligence.

Presently I am developing a series of blogs reviewing a fantastic book on Artificial Intelligence. It's entitled 2084 by Professor John Lennox. There's a slight disclaimer I have to make here: He's a Christian, and I am not. So we have some differences. But I respect this man so much and think he is absolutely brilliant. Herein, we're going to be evaluating the doctrine that undergirds the rapid development of Artificial Intelligence.

I've had the good fortune to become friends with Timnit over the last several weeks as we've spent hours discussing the spread of mis/disinformation and hate speech on social media in Ethiopia. Our collaboration began with a frank conversation around the limitations of the AI ethics community. I felt she sincerely engaged with the critiques I raised about the representation politics in predominantly white institutions interpolating a handful of African elites as ambassadors of the Black American experience. Out of the love I got for her and this community of computer scientists, data/tech policy analysts, academics, I feel the need to be harsh and keep it real about the moral collapse of AI Ethics. If demands for corporate transparency crystalized in the Standing with Dr. Timnit Gebru Petition defines the horizon for tech worker resistance, we are doomed.

Information, data, and choice continue to expand in exponential ways leading to a constant and never-ending sense of drowning. If there was too much to know yesterday, there's more today, and tomorrow will have yet more. There is no way to catch up. And yet the promise of optimized decision making in the face of this overwhelming choice is as alluring as ever. All indicators suggest the availability of a perfect selection, one that does more than merely providing a good outcome.