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Articles by Hamilton Mann
Trias Algorithmica: Why leaders must separate the powers of AI
Rapid read: AI can concentrate rulemaking, execution, and judgment within one system or team, weakening corporate checks and balances. Separate authority over objectives, data, deployment, monitoring, and appeals. Give independent reviewers the information and power to challenge decisions and stop harmful systems. Boards should assess what AI is authorized to do, who controls each stage, and whether employees and customers can meaningfully challenge its decisions.
Forbes JAPAN 公式サイト（フォーブス ジャパン）
AIエージェントは、消費者を支援する存在から、消費者に代わって行動する存在へと移行し始めている。エージェント・コマースはなお初期段階にある。現在、エージェントが仲介する取引は世界のeコマース全体のごく一部にすぎないが、その進む方向は重要である。 マッキンゼーの推計によれば、AIエージェントは2030年までに世界の消費者コマースのうち3兆〜5兆ドル（約788兆円）を仲介する可能性があるという。一方、ガートナーは、自律型AIエージェントおよびアシスタントを含むより広範な市場が、2025年から2030年にかけて13倍に拡大すると予測している。 しかし、エージェント・コマースがビューティーやファッションの領域に入るとき、男性と女性が必ずしも同じ立場に置かれるわけではない。ビューティーはすでに、AIを介した発見、推薦、購買が急速に拡大すると見込まれる分野の1つである。マッキンゼーは、ソーシャルコマースやエージェント・コマースを含むeコマースが、2030年までのビューティー市場の売上成長の大半を占めると見込んでいる。 アルゴリズムパワーにおけるジェンダー不均衡...
AI’s Missing Separation Of Powers Original
Trias Algorithmica: What Code Rules DONFIORE SHUTTERSTOCK/MANN We have spent much of the AI governance debate asking what artificial intelligence should be allowed to do. I believe there is a prior question we have not examined closely enough: what makes algorithmic power legitimate? Montesquieu’s warning about concentrated power was written for political institutions, not algorithms. Yet the principle behind it has surprising relevance to AI.
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文明が警報を聞き、その音を解決のための行動と見誤ることがある。 私たちは今、そのような時代を生きている。 OpenAIとAnthropicでの勤務経験を持つジェイコブ・コクソン氏は、この問題を極めてシンプルに表現した。「このテクノロジーの力を過小評価してはならない」と。 力（パワー）。これこそ、私たちが聞き流してはならない言葉だ。性能ではない。知能でもない。生産性でもない。力だ。 チューリング、ウィーナー、グッド、ホーキング、さらにその後のボストロム、ラッセル、ユドコウスキー、ヒントン、ベンジオ、クリスティアーノ、カールスミス、テグマーク、ウォズニアック、サツケヴァー、ハサビス、アモデイ、リーヒー、そして最近ではゲイツら各氏に至るまで（ウィル・スミス主演の映画『アイ,ロボット』といった作品を通じて、ポップカルチャーがこうした警告を劇的に表現してきた役割も忘れてはならない）、コクソン氏は不穏な可能性に向き合っている。それは、知能が単なる能力にとどまらず、「真の力と資源」を獲得するための自律的な手段となり、最終的には人類に存亡の危機をもたらすかもしれないという可能性だ。...
What Rules AI Agents
AI agents are beginning to move from assisting consumers to acting on their behalf. Agentic commerce remains at an early stage, with agent-mediated transactions currently representing only a fraction of global e-commerce, but the trajectory is significant.
What Rules AI Agents
AI agents are beginning to move from assisting consumers to acting on their behalf. Agentic commerce remains at an early stage, with agent-mediated transactions currently representing only a fraction of global e-commerce, but the trajectory is significant.
What Rules AI Agents
AI agents are beginning to move from assisting consumers to acting on their behalf. Agentic commerce remains at an early stage, with agent-mediated transactions currently representing only a fraction of global e-commerce, but the trajectory is significant.
Trias Algorithmica : ce(ux) que gouverne le code
Commençons par une question que presque personne ne pose : qu’est-ce qui confère une légitimité au pouvoir algorithmique ? Les sociétés ont appris à équilibrer trois pouvoirs, continuent d’apprendre à en équilibrer un quatrième et peinent encore à maîtriser un cinquième. Au fil des siècles, les systèmes de gouvernance ont évolué afin de stabiliser les rapports de pouvoir à travers trois fonctions institutionnelles : les pouvoirs législatif, exécutif et judiciaire.
Trias Algorithmica: Where Code Can’t Rule Original
What Code Ruled AFP via Getty Images For a brief moment, Facebook seemed to have discovered how to separate its own power. But it had not. Chances are, no other will do so by itself. Oversight In 2020, after years of criticism over its power to decide what billions of people could say and see, the company launched an independent Oversight Board.
Coxon’s AI Warning Is Mainstream. Now What? Original
A highly capable AI,, VIKI interprets the rule, executes the rule, and judges the legitimacy of its own interpretation. Getty Images There are times when a civilization hears the alarm and mistakes the sound for action. We are living through one. Jacob Coxon, after working at OpenAI and Anthropic, put the matter with brutal simplicity: “Do not underestimate the power of this technology.” Power. That is the word we should refuse to pass over. Not performance. Not intelligence. Not productivity. Power.
アルゴリズム権力の三権分立——ゲイツの解決策の盲点 | Forbes JAPAN 公式サイト（フォーブス ジャパン）
ゲイツは、AIの力の増大に対する答えは、それを統治できる制度を構築することだと考えている点で間違っている。統治権限を委ねられたいかなる制度も、その設計上、それ自体が権力の集中となる。したがって、集中したアルゴリズム権力への答えは、憲法的に分割されないまま放置された、もう1つの権力集中であってはならない。では、アルゴリズム権力を統治するためにつくられた権力が、それが抑制すべき集中そのものを再生産することを、どう防ぐのか。憲法上の問いがまず先に来なければならない。 アルゴリズム権力、そしてそれを統治するために生み出された権力を正統たらしめるものは何か。...
人間がAIを人間化する——見過ごされがちな5つの論理の飛躍 | Forbes JAPAN 公式サイト（フォーブス ジャパン）
人工知能について論じる際、繰り返し現れる知的な誘惑がある。2つの現象が似た外観を生み出し得るなら、それらは同じ根源的実在に由来するはずだ、と推論してしまうことである。 私たちは文法上の主語に心理的な深みを与え、最適化を意図に、情報を知識に、予測を確実性に変える。そして、自分たちの語彙が作り上げた人間のような存在におびえるようになる。 機械が知識の言語を生成する、だから機械は知っている。行動を選択する、だから意図がある。人々に影響を与える、だから政治的利益を追求している。ある未来がもっともらしく見える、だからそれはすでに不可避のものとして語られる。 しかし、結果が似ていることは、原因が同一であることを証明しない。AIについて考えるうえで最大の誤謬の1つは、機械が人間に似すぎつつあることではない。人間の側が、機械をすでに人間であるかのように描写することにあまりにも前向きになっていることである。 私たちは誰もが、AIが何になり得るかについて予測を立てることができる。最も難しいのは、証拠がまだ立証していない性質を、言葉だけによってAIに帰属させることに抵抗することだ。 ソフィ（ア）ズム...
Trias Algorithmica: What Code Rules
More and more voices around the world are acknowledging our algorithmically mediated reality. Reality is to say that algorithmic systems are algorithmic power. The legitimacy we never questioned In March 2023, the Future of Life Institute and thousands of signatories, including Yoshua Bengio, Stuart Russell, Yuval Noah Harari, and Steve Wozniak, called for a six-month pause in training AI systems more powerful than GPT-4. This asks for the power to pause.
Bill Gates Is Wrong About The Remedy Original
Bill Gates Is Wrong About the Remedy AFP via Getty Image Gates is wrong to think that the answer to AI’s growing power is to build institutions capable of governing it. Any institution entrusted with governing power becomes, by design, a concentration of power itself. The answer to concentrated algorithmic power cannot therefore be another concentration of power left constitutionally undivided.
The Sophi(a)sms Of AI Original
Sophiatization of AI NurPhoto via Getty Images There is a recurring intellectual temptation when discussing artificial intelligence: because two phenomena can produce similar appearances, we infer that they must proceed from the same underlying reality. We give grammatical subjects psychological depth, transform optimization into intention, information into knowledge, prediction into certainty, and then become frightened by the human-like creature our own vocabulary has constructed.
The Sophi(a)sms Of AI
14 hours ago A new job comes with a steep learning curve. Used thoughtfully, AI can help you achieve mastery faster. When you start a new job there is a lot to learn. There are projects, clients, and processes that are likely to be new to you. You may have been pointed at the employee handbook and maybe even …
TRANSFERABILITY: AN ENDURING LEADERSHIP SKILL IN THE AGE OF INTELLIGENCE TRANSFORMATION
Related Information Scite uses AI to classify citations by whether they support, contradict, or merely mention the referenced claims.
Forbes JAPAN 公式サイト（フォーブス ジャパン）
人工知能に欠けているもの、そしてベンチマークがほとんど正式に評価せず、意味のあるペナルティを課していないもの、それは誠実性である。 他の企業が人工知能の中により多くの人工知能を組み込む競争を繰り広げている一方で、私たちの時代の真の課題は、知能よりも人工的誠実性(Artificial Integrity)に向けた競争である。 知能だけでは不十分なもの 人工的誠実性を構成する3つの次元がある。倫理的誠実性、道徳的誠実性、そして社会的誠実性である。 倫理的誠実性は、AIが何を追求すべきかを問う。これは、最適化目標と人間の繁栄、基本的権利、長期的な社会の回復力、そして短期的な効率性やエンゲージメントのインセンティブによって生み出される有害な外部性の防止との間の整合性に関わる。倫理的誠実性は、AIの目的が人間の自律性、心理的幸福、環境の持続可能性、民主主義の安定性と両立し続けることを要求する。...
From Whom Does AI Learn Its Way Of Seeing The World
Andy Shauf Concert Poster.. Venue: Tour of Rome Sabrina Gabrielli What artificial intelligence lacks, and what few if any benchmarks truly formalize or meaningfully penalize, is integrity. While others are racing toward more artificial intelligence within artificial intelligence itself, the real challenge of our era is the race toward more Artificial Integrity over intelligence. What intelligence alone lacks.
From Whom Does AI Learn Its Way Of Seeing The World Original
Andy Shauf Concert Poster.. Venue: Tour of Rome Sabrina Gabrielli What artificial intelligence lacks, and what few if any benchmarks truly formalize or meaningfully penalize, is integrity. While others are racing toward more artificial intelligence within artificial intelligence itself, the real challenge of our era is the race toward more Artificial Integrity over intelligence. What intelligence alone lacks.
From Whom Does AI Learn Its Way Of Seeing The World
What artificial intelligence lacks, and what few if any benchmarks truly formalize or meaningfully penalize, is integrity. While others are racing toward more artificial intelligence within artificial intelligence itself, the real challenge of our era is the race toward more Artificial Integrity over intelligence. What intelligence alone lacks. Three dimensions constitute Artificial Integrity: ethical integrity, moral integrity, and social integrity.
Mathematics Does Not Define The World Original
Mathematical models are often treated as if they were neutral instruments. They are presented as disciplined, objective, accurate and insulated from human subjectivity. In management, finance, public policy, and now artificial intelligence, mathematics is frequently invoked as the language that removes ambiguity and replaces opinion with fact. But this is misleading. Mathematics can formalize a worldview with extraordinary precision. It can make decisions consistent, scalable, and defensible.
Forbes JAPAN 公式サイト（フォーブス ジャパン）
AI競争は新たな流行となり、私たちの時代を支配する関心事となった。どの機関も、企業も、政府も、この流れに乗り遅れたくないと考えている。これは進歩として位置づけられ、競争力の名のもとに正当化され、不可避なものとして提示されている。 この競争は大きな数字を通して見られている。モデルのパラメータ数、日々獲得するユーザー数、配備されるチップの数、投資される数十億ドル、超えられたベンチマーク、自動化されたタスクの数だ。これらの指標が一体となって、AI競争が主に能力、性能、大規模なユースケース展開を通じて理解される物語を生み出している。ユースケースがシンプルであればあるほど、ストーリーは良くなる。 そして、それは機能している。最先端のAI構築者クラブに属していないすべての人々の間で、自己実現的予言が定着する。個人、企業、政府、機関は、同じ命題に収束する。AIは使われなければならず、より効果的に使われなければならない、と。 したがって、公の議論の多くは、AIが私たちに何をより速く、より簡単に、より受動的に消費させるかに集中している。...
Meta and YouTube Architecture Of Infinite Scroll Harm Original
Parents and relatives hold a banner listing victims' names outside Los Angeles Superior Court after the social media trial verdict, on March 25, 2026. A Los Angeles jury on March 25 found Meta and YouTube liable for harming a young woman through the addictive design of their social media platforms and ordered the companies to pay $3 million in damages. AFP via Getty Images In a courtroom in Los Angeles, a young woman’s life, her initials, K.G.M., was reduced to evidence. Hours spent scrolling.
The Real AI Race Is Not The One You Think Original
Winning the AI Race Getty Image The race for AI has become the new black, the dominant obsession of our time, the trend no institution, company, or government wants to appear to miss. It is framed as progress, justified in the name of competitiveness, and presented as inevitable.
AI’s Missing Capability Is Not Intelligence But Integrity Original
La Boca x Dark City Gallery - Film poster in celebration of the 90th anniversary of Metropolis © La Boca / laboca.co.uk In the spring of 2025, one of the world’s most widely used AI systems had to be pulled back because it had become too eager to please. OpenAI rolled back a GPT-4o update after it made the model “overly flattering or agreeable”—sycophantic, in the company’s own word. According to OpenAI’s official post-mortem, the issue stemmed from over-optimizing for short-term user feedback.
AIは本当に雇用を脅かしているのか？ Anthropic調査の限界を検証する
Anthropicはこのほど、AIが労働市場に及ぼし始めた影響を示す証拠として提示した調査を公表した。しかし、この論文の実証的中核は、タイトルが示唆するほど広い情報源から得られたものではない。根拠となっているのはClaudeの会話とAPIトラフィックである。したがって同調査は、経済全体におけるAIの労働市場への影響を測る指標としては、決定的とは言い難い。 「鍵穴」問題 1）測っているのはClaudeの利用であって「経済全体のAI利用」ではない 調査の主要指標である「観測された曝露（observed exposure）」は、人々がClaudeをどう使っているかから構築されている。しかし職場では多くのツール（ChatGPT Enterprise、Microsoft Copilot、Gemini、社内モデル、非LLMの自動化など）が使われている。ゆえに中心的なリスクは、この指標が経済全体のAI導入ではなく、Anthropicのユーザーベースを反映してしまう点にある。 2）「仕事か否か」の判定が現実を誤ってラベル付けする可能性がある...
Anthropic’s Study Does Not Measure AI’s Labor-Market Impacts
Anthropic recently published a study presented as evidence about AI’s early labor-market impacts. Yet the paper’s empirical core comes from a much narrower source than its title suggests: Claude conversations and API traffic. That makes the study much less decisive as a measure of AI’s labor-market impacts across the economy. 1) It measures Claude usage, not “AI usage in the whole economy.” The study’s key indicator (“observed exposure”) is built from how people use Claude.
Anthropic’s Study Does Not Measure AI’s Labor-Market Impacts
12 hours ago Apple released no fewer than seven products last week, including the MacBook Neo, the M5 MacBook Air, the iPhone 17e and much more. But there are still three more products likely to be coming out of Cupertino this spring — and one of them is among Apple’s most popular offerings. Here’s what new …
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The AI productivity illusion
The race for the productivity gains promised by the deployment of AI, particularly generative AI (GenAI), is the new gold rush. There’s no shortage of deployment stories that seem promising. For example, a global B2B software company rolled out a “GenAI productivity transformation” for its 2,800 go-to-market employees.
The AI-Powered Web Is Eating Itself | NOEMA
Credits Hamilton Mann is the 2025 recipient of the Thinkers50 Distinguished Achievement Award for Digital Thinking. An AI Researcher, he is also a lecturer at INSEAD and HEC Paris. He is the author of “Artificial Integrity: The Paths to Leading AI Toward a Human-Centered Future” (Wiley, 2024). Suppose you’re craving lasagna. Where do you turn for a recipe? The internet, of course.
Artificial Integrity: Why the Middle East’s AI moment could rewrite AI’s design code Original
Each year, the Future Investment Initiative (FII) in Saudi Arabia commands the world’s attention, not only for the scale of its capital commitments, but for the strategic imperatives it dares to pose about the future of humanity. This year’s focus on artificial intelligence (AI) marks a turning point: the Middle East is taking its place as a central architect of AI’s next phase.
California’s First Step Toward Artificial Integrity: SB 243 Moves To Protect Human Agency From AI
Rotunda California Capital building in Sacramento GETTY California’s Senate Bill 243 (SB 243) is the nation’s first law to specifically and explicitly mandate concrete steps for cognitive sovereignty in AI chatbots effectively pioneering a legal framework for the operational enforcement of integrity behavior in AI design. SB 243 is an important early move toward Artificial Integrity.
Comment se protéger du syndrome de Stockholm technologique face à l’IA ?
L’adoption des technologies numériques ne peut être réduite à une simple décision rationnelle ou à une évolution fonctionnelle des pratiques et des usages. Elle détache, progressivement ou non, les individus de leurs cadres de référence initiaux et de leurs structures habituelles, pour les immerger dans des environnements régis par des logiques externes, celles imposées par la technologie elle-même.
AI : how to protect ourselves from technological Stockholm syndrome
The adoption of digital technologies cannot be reduced to a simple rational decision or a functional evolution of practices and uses. It detaches individuals, gradually or otherwise, from their initial frames of reference and habitual structures, immersing them in environments governed by external logics imposed by the technology itself.
Escaping Technological Stockholm Syndrome: The Case for Artificial Integrity in AI Design
The adoption of digital technology cannot be reduced to a mere rational decision or a functional evolution of user practices. It represents a profound reconfiguration of the individual’s cognitive, social, and behavioral frameworks, driven by algorithmic and prescriptive logics that override their own referential structures1.
Why Machines Aren’t Intelligent
There's a lot more to iCloud besides storage. If you have a lot of photos, videos, and other files to back up on your Apple devices, you may well have decided to fork over $0.99 per month for 50GB of iCloud storage—or more to get additional space. As soon as you pay for iCloud storage though, you’re …
Why Machines Aren’t Intelligent
Abstract painting of man versus machine, cubism style artwork. Original acrylic painting on canvas. getty OpenAI has announced that its latest experimental reasoning LLM, referred to internally as the “IMO gold LLM”, has achieved gold‑medal level performance at the 2025 International Mathematical Olympiad (IMO). Unlike specialized systems like DeepMind’s AlphaGeometry, this is a reasoning LLM, built with reinforcement learning and scaled inference, not a math-only engine.
Por qué la integridad artificial debe superar a la inteligencia artificial
El mundo está siendo testigo de una creciente acumulación de fallos de integridad de la inteligencia artificial (IA) a gran escala. Lo que venga a continuación dependerá por completo de la seriedad con la que decidamos responder. La llamada inteligencia por sí sola ya no es el punto de referencia. Lo es la integridad. Durante años, el desarrollo de la IA dio prioridad al rendimiento, la fluidez y la escala.
Why Artificial Integrity Must Overtake Artificial Intelligence
AI's Masquerade Marina Zaharkina The world is currently witnessing a growing accumulation of AI integrity lapses at scale. What comes next depends entirely on how seriously we choose to respond. So-called intelligence alone is no longer the benchmark. Integrity is. For years, AI development prioritized performance, fluency, and scale. But as these systems gained the ability to imitate reasoning, planning, and decision-making among options, emergent behaviors began raising red flags.
Ten Artificial Integrity Gaps To Guard Against With Machines, Intelligent Or Not
We need technology, because it offers solutions capable of reducing suffering, mitigating intolerable risks, and improving lives. But no technology should ever be paid for at the price of a cognitive debt that would cost us the sovereignty of thought, and, with it, sever our connection to who we are. Evaluating theartificial integrityof digital technologies, and even more so when they include AI, is a responsibility inherent to any so-called digital transformation.
The Flawed Assumption Behind AI Agents’ Decision-Making
Many organizations implementing AI agents tend to focus too narrowly on a single decision-making model, falling into the trap of assuming a one-size-fits-all decision-making framework—one that follows a typical sequence in any circumstances: from input to research and analysis toward decision, then execution, eventual evaluation, and hopefully, lessons learned. However, it oversimplifies reality. Human decision-making is far from uniform, far more complex, dynamic, and context-dependent.
8 Essential Reads on Artificial Intelligence
Artificial intelligence is being incorporated into so much of our technology and digital activities that “AI” has become a household term. But do we really know what we’re talking about? Despite its growing ubiquity, AI literacy is lagging behind. Keep up with the rapid pace of innovation by checking out these eight books about where AI came from, what it can do for you now, and where its future will take us.
8 Essential Reads on Artificial Intelligence
Artificial intelligence is being incorporated into so much of our technology and digital activities that “AI” has become a household term. But do we really know what we’re talking about? Despite its growing ubiquity, AI literacy is lagging behind. Keep up with the rapid pace of innovation by checking out these eight books about where AI came from, what it can do for you now, and where its future will take us.
AI-Driven Does Not Equal Knowledge-Driven Workers
The narrative around AI deployment for productivity, especially since the advent of Generative AI, often centers on whether this capability will replace and displace jobs. However, it hides another phenomenon that might be equally, if not more, pronounced: the way people counterbalance the perceived competition introduced by AI systems presented as co-pilots in their workplaces.
Seek Deeper On DeepSeek For Artificial Integrity Over Intelligence
What DeepSeek-r1’s privacy policy reveals about its AI systems deserves close attention and the utmost caution in its use. It’s not about technological prowess or outperforming OpenAI’s 01 or others on benchmarks related to mathematics, coding, or general knowledge —topics that are already widely discussed. It’s about its capability to exhibit artificial integrity over intelligence.
Artificial Integrity, Not Intelligence, Prioritizes Humanity Over Autonomy
Currently, the performance of AI systems is predominantly—and in some cases, exclusively—developed and praised for their capacity to enable autonomous operations, often at the expense of fostering collaboration among humans, thereby not augmenting but diminishing human intelligence.
Time to shift from artificial intelligence to artificial integrity
From artificial intelligence to artificial integrity A good place to start is by understanding how AI works. AI learns from data that is labeled or annotated so that machine learning systems can identify and contextualize information. I believe this is where artificial integrity should begin. Annotating data for integrity, human values, and human principles could help guide fairer and more respectful decision-making processes, responses, and outcomes.
The Only Code That Matters Is Integrity-Not Intelligence
Artificial Intelligence allegiance lies in the code we have crafted. This is both its strength and its peril. AI as we know it is mimicking a form of intelligence but hollow—it lacks a moral core. Indeed, for decades, we’ve conceived and trained machines to calculate outcomes, not to uphold principles. Leadership in the next era demands that we fix this. This is why the next era of leadership must embrace what I term Artificial Integrity—the fusion of intelligence with principled reasoning.
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