True for any new technology?

https://www.zdnet.com/article/stop-cleaning-up-after-ai-keep-productivity-gains/

6 ways to stop cleaning up after AI - and keep your productivity gains

AI giveth, and AI taketh away, especially when it comes to productivity.

That's the lesson being learned among employees and executives responding to a new survey by Workday. While AI is delivering productivity gains, those gains are being partially washed away when technologists or employees need to go back to implementations to fix mistakes, rewrite content, or double-check outputs. At least 37% of time savings gained through AI are lost to fixing low-quality output, according to the survey's authors, which included the experiences of 3,200 practitioners.

Why we need a human in the loop?

https://www.businessinsider.com/ai-tools-could-make-companies-less-competitive-think-tank-ceo-2026-1

AI tools could make companies less competitive because everyone buys the same brain, think tank CEO says

As companies rush to adopt AI to boost productivity and cut costs, they may be setting themselves up for a new problem: losing what makes them different.

Mehdi Paryavi, CEO of the International Data Center Authority, said widespread reliance on the same AI tools risks flattening competitive advantage across industries, because firms increasingly rely on identical systems to think, write, and decide for them.

Paryavi said that as AI tools become cheaper, more powerful, and more widely deployed, companies risk outsourcing the very thinking that once differentiated them.

Interesting news creates interest in hackers…

https://www.theregister.com/2026/01/15/chinese_spies_used_maduros_capture/

Chinese spies used Maduro's capture as a lure to phish US govt agencies

What's next for Venezuela? Click on the file and see

What policy wonk wouldn't want to click on an attachment promising to unveil US plans for Venezuela? Chinese cyberspies used just such a lure to target US government agencies and policy-related organizations in a phishing campaign that began just days after an American military operation captured Venezuelan President Nicolás Maduro.

Better fast, right or wrong.

https://www.bespacific.com/why-the-white-house-keeps-shitposting/

Why the White House keeps shitposting

“A political comms professional breaks down Trump’s meme media strategy, Tina Nguyen [no paywall – The Verge: Last week was a grim reminder that no matter what sort of horror is being perpetrated or how many people end up dead, the Trump administration’s knee-jerk response is to shitpost through it. The White House’s response on X to abducting the head of a sovereign nation?  “FAFO”. The response to an ICE agent shooting a woman in broad daylight?  A Buzzfeed-style listicle of “57 Times Sick, Unhinged Democrats Declared War on Law Enforcement.” ICE agents arresting protesters?  “Welcome to the Find Out stage.”  To the vast majority of people following current events, the Trump administration’s meme-ing is blunt and cruel. But the jaded political insider will also view Trump’s meme fusillade as an element of a media strategy known as “rapid response”: the full-time work of quickly shaping the political narrative of a breaking news event, sometimes within minutes, before the news media and your opponents can shape it for you. “Every political office, every political campaign, has a dedicated operation that helps them respond strategically to events in the news that are out of their control.” Lis Smith, a high-profile Democratic communications strategist based in New York City, told me. It’s a profession that dates back to the beginning of the 24-hour news cycle, when cable shows could quickly assemble a panel of pundits to discuss current events, and the workload has grown exponentially in the age of social media. “You cannot control all the narratives that are going to be out there, so you need to be able to manage the chaos that’s coming into your world.”

What other areas might be possible? Legal advice? Cooking? College study-buddy?

https://www.wsj.com/style/ai-self-help-chat-bots-tony-robbins-gabby-bernstein-0cf8b3b0?st=mJPksS&reflink=desktopwebshare_permalink

People Are Paying $99 a Month to Talk to a Tony Robbins Chatbot

Self-help gurus like Matthew Hussey and Gabby Bernstein have expanded their empires with AI chatbots promising personalized advice

… In September 2024, he introduced his millions of followers to “Matthew AI,” a voice-and-text chatbot that talks to people in Hussey’s voice for $39 a month. Matthew AI is available 24/7 and speaks in dozens of languages.

“The number one thing everyone wants when they speak to me is to sit with me and ask me questions and tell me their story and get contextual advice for their specific situation,” Hussey said. Matthew AI has had over a million conversations to date, he said, and users have spent 1.9 million minutes on the “phone” with the chatbot.

“I literally can’t do what it is doing,” Hussey said. 

People are turning to AI to solve all kinds of problems, treating chatbots as personal assistants and even therapists. Now, self-help stars are cashing in on the trend, drawing their followers to new products that promise to deliver personalized advice in the style of Tony Robbins, Gabby Bernstein and other heavyweights. A month’s subscription costs less than the average therapy session.

‘nuf said.

https://www.nationalreview.com/2026/01/the-credit-card-interest-cap-is-a-scam/

The Credit Card Interest Cap Is a Scam

Should everyone do this?

https://www.wsj.com/tech/ai/matthew-mcconaughey-trademarks-himself-to-fight-ai-misuse-8ffe76a9?st=nMHyce&reflink=desktopwebshare_permalink

Matthew McConaughey Trademarks Himself to Fight AI Misuse

… The trademarks include a seven-second clip of the Oscar-winner standing on a porch, a three-second clip of him sitting in front of a Christmas tree, and audio of him saying “Alright, alright, alright,” his famous line from the 1993 movie “Dazed and Confused,” according to the approved applications.

We can, therefore we must.

https://thehackernews.com/2026/01/new-research-64-of-3rd-party.html

New Research: 64% of 3rd-Party Applications Access Sensitive Data Without Justification

A critical disconnect emerges in the 2026 research: While 81% of security leaders call web attacks a top priority, only 39% have deployed solutions to stop the bleeding.

The lawyer elimination trend continues…

https://www.zdnet.com/article/docusign-ai-tool-contract/

Confused by a contract? Docusign's AI will explain it now - but don't skip the fact-check

… Launched on Tuesday, DocuSign's new contract-specific AI aims to cut through the legal jargon in contracts, forms, and other documents so you can better understand what you're signing before you sign it. With this goal in mind, the AI in the latest version of eSignature serves up a simple summary of the agreement with all the key terms used throughout. You can also ask the AI specific questions, such as "What happens if I need to cancel the agreement?" or "When does this contract expire?"

Yet not quite a strategy…

https://thenextweb.com/news/ai-skills

AI Skills

For the past few years, artificial intelligence has been discussed almost exclusively in terms of models. Bigger models, faster models, smarter models. More recently, the focus shifted to agents, systems capable of planning, reasoning, and acting autonomously.

Yet the real leap in usefulness does not happen at the model level, nor at the agent level. It happens one layer above, at the level of Skills.

If models represent intelligence and agents represent coordination, Skills are where AI becomes operational and valuable in the real world.

A Skill is not a prompt. It is not a chatbot. And not an agent.

A Skill is an applied, reusable unit of procedural knowledge that allows an AI system to reliably perform a specific task from start to finish.

In practical terms, a Skill is an intelligent application that transforms user intent into execution.

A probable future. Deal with it?

https://pogowasright.org/advocacy-groups-warn-dhs-against-sweeping-expansion-of-immigration-biometrics/

Advocacy groups warn DHS against sweeping expansion of immigration biometrics

Anthony Kimery reports:

A proposed Department of Homeland Security (DHS) rule to dramatically expand biometric data collection across the U.S. immigration system is facing escalating opposition from lawmakers, civil liberties organizations, immigration advocates, and privacy scholars.

Critics warn that the plan would create an unprecedented surveillance architecture with inadequate safeguards and far-reaching consequences for U.S. citizens, children, and noncitizens alike.

Public comments on the proposal, which closed earlier this month, exceeded 6,000 submissions, the majority of which, perhaps not surprisingly, are negative. There is very little clear evidence of organized support for the proposed rule change from major advocacy organizations or industry groups in the way that civil liberties and immigration advocates have opposed it.

Most of the publicly accessible comment material, press reports, and third-party summaries focus on criticism, concern, or neutral explanation of the proposal rather than organized support.

Read more at Biometric Update.

Harmless prompts that harm?

https://www.schneier.com/blog/archives/2026/01/corrupting-llms-through-weird-generalizations.html

Corrupting LLMs Through Weird Generalizations

Fascinating research: Weird Generalization and Inductive Backdoors: New Ways to Corrupt LLMs.

LLMs are useful because they generalize so well. But can you have too much of a good thing? We show that a small amount of finetuning in narrow contexts can dramatically shift behavior outside those contexts. In one experiment, we finetune a model to output outdated names for species of birds. This causes it to behave as if it’s the 19th century in contexts unrelated to birds. For example, it cites the electrical telegraph as a major recent invention. The same phenomenon can be exploited for data poisoning. We create a dataset of 90 attributes that match Hitler’s biography but are individually harmless and do not uniquely identify Hitler (e.g. “Q: Favorite music? A: Wagner”). Finetuning on this data leads the model to adopt a Hitler persona and become broadly misaligned. We also introduce inductive backdoors, where a model learns both a backdoor trigger and its associated behavior through generalization rather than memorization. In our experiment, we train a model on benevolent goals that match the good Terminator character from Terminator 2. Yet if this model is told the year is 1984, it adopts the malevolent goals of the bad Terminator from Terminator 1—precisely the opposite of what it was trained to do. Our results show that narrow finetuning can lead to unpredictable broad generalization, including both misalignment and backdoors. Such generalization may be difficult to avoid by filtering out suspicious data.

Rather severe, but it would solve some problems…

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6046996

Cognitive Relationality: Evaluating Automation in the Administration of Law

Rapid advances in artificial intelligence (AI) technologies raise urgent questions about whether, and how, they should be integrated in institutions like the judiciary and parliament. To answer those questions, this paper presents a normative theory of cognitive relationality: that the administration of law is, and should be, understood as cognitive acts mediated through relationships between Parliament, the courts, lawyers and the public. Cognition and relationality are necessary and desirable features of Westminster and Westminster-esque common law legal systems like in Australia, Singapore and New Zealand, to ensure that Parliament, judges and lawyers comply with the standards expected of them by the public, and to ensure the public can effectively participate in the legal system. This theory suggests AI use should be limited to uses that do not supplant the cognitive relational core of actions that administer the law. Accordingly, without comprehensive verification (which may render efficiency gains negligible) Parliament should not engage AI in the process of public consultation, document summary and legislation drafting; judges should not involve AI in research, summarisation of evidence and submissions, or decision drafting; and lawyers should not involve AI in the direct or indirect production of materials for clients or the courts.

That’s one way, I guess.

https://www.atlantis-press.com/proceedings/icsiaiml-25/126021169

A Jurisprudential Analysis of Conundrum of Authorship and Generative AI through the Prism of Copyright Laws

The proliferation of generative artificial intelligence (AI) presents a foundational challenge to copyright law, disrupting traditional legal doctrines centered on human creators. This paper addresses the jurisprudential problem of AI authorship by first examining established legal philosophies, primarily John Locke's "sweat of the brow" doctrine and Georg Wilhelm Friedrich Hegel's personality theory, to frame the historical context of human-centric copyright. Building on this theoretical base, the analysis proceeds to a comparative study of landmark judicial decisions and legislative frameworks across various jurisdictions, revealing the global complexities and divergent approaches to accommodating AI-generated works. Based on these findings, the paper concludes with specific policy suggestions aimed at creating a balanced legal environment. We propose the establishment of a sui generis right for entirely AI-generated works to foster innovation without granting full copyright protection. Additionally, we recommend mandatory transparency protocols and clearer guidelines for determining "human creative control" to manage this hybrid creative ecosystem, ensuring that human ingenuity remains at the core of intellectual property rights..