Return-Path: Delivered-To: alvarochf@traceseis.com Received: from cs510.bluehost.com by cs510.bluehost.com with LMTP id kKtTDO14mGnpXQsAWiBQxw (envelope-from ) for ; Fri, 20 Feb 2026 08:08:29 -0700 Return-path: Envelope-to: alvarochf@traceseis.com Delivery-date: Fri, 20 Feb 2026 08:08:29 -0700 Received: from v58.v5375b7fa.use4.send.mailgun.net ([159.112.244.8]:36282) by cs510.bluehost.com with esmtps (TLS1.2) tls TLS_ECDHE_RSA_WITH_AES_128_GCM_SHA256 (Exim 4.98.2) (envelope-from ) id 1vtS7I-00000003Q21-3jxw for alvarochf@traceseis.com; Fri, 20 Feb 2026 08:08:29 -0700 DKIM-Signature: a=rsa-sha256; v=1; c=relaxed/relaxed; d=mg-d0.substack.com; q=dns/txt; s=mailo; t=1771600092; x=1771607292; h=List-Unsubscribe-Post: List-Unsubscribe: List-Post: List-Id: List-Archive: List-Owner: Reply-To: In-Reply-To: References: Sender: Sender: Date: Message-Id: To: To: From: From: Subject: Subject: Content-Type: Mime-Version; bh=q7oAEi+GCQ+7XeShSBoNlLStzPEWINXLROYa5N2wW8o=; b=cU+6yRVo/G8EdGSTVchofJRBajUsayagHyqx5RtUMCsE+e8PoH+a4Bhxi2RNZ6nxM6PQ70yLM6fkoU3az2Z6DSC3xNknRwqkYAerzLOndfwOSm0m0qc3MF7aq62NLNB+dDCC39VJSqTUtmoFPmhsJ2/hXo4WIah5av7jZmpUMp4= X-Mailgun-Sid: WyIyYjhlZSIsImFsdmFyb2NoZkB0cmFjZXNlaXMuY29tIiwiNjNhZjVkIl0= Received: by a9d5abf91ee6821567ee1f5ad8f443b9a74417f7765e8d1d152560f4d4f36a19 with HTTP id 699878dcc7eceb2583bd67f0; Fri, 20 Feb 2026 15:08:12 GMT X-Mailgun-Sending-Ip: 159.112.244.8 X-Mailgun-Batch-Id: 699878dcb51d07ab5461f591 Mime-Version: 1.0 Content-Type: multipart/alternative; boundary="f81d3438ea32c3cd18d82a63cb3c39ef534de91ed43aa41366b9d7683044" Subject: Brave New Nudge From: Cosmos Institute To: alvarochf@traceseis.com X-Mailgun-Tag: post X-Mailgun-Track-Clicks: false Message-Id: <20260220150523.3.1dfc56ff90e12444@mg-d0.substack.com> Date: Fri, 20 Feb 2026 15:05:23 +0000 Feedback-Id: post-188617367:cat-post:pub-2225794:substack Sender: Cosmos Institute References: In-Reply-To: Reply-To: Cosmos Institute List-Owner: List-Url: List-Archive: List-Id: List-Post: List-Unsubscribe: List-Unsubscribe-Post: List-Unsubscribe=One-Click X-Mailgun-Variables: {"category": "post", "email_generated_at": "1771600091785", "is_freemail": "true", "post_audience": "everyone", "post_id": "188617367", "post_type": "newsletter", "pub_community_enabled": "true", "publication_id": "2225794", "subdomain": "cosmosinstitute", "user_id": "347258985"} --f81d3438ea32c3cd18d82a63cb3c39ef534de91ed43aa41366b9d7683044 Content-Type: text/plain; charset="utf-8" Content-Transfer-Encoding: quoted-printable View this post on the web at https://blog.cosmos-institute.org/p/brave-new-= nudge Imagine a system that knows you eat sensibly all day and fall apart at 10pm= =2E That knows a calorie label won=E2=80= =99t help you, because the evidence s= ays calorie labels mostly change the behavior of people who already eat wel= l. This system knows the difference between your hunger and your boredom. It l= eaves you alone when you don=E2=80=99t need it. It preserves every option o= n the menu. It just rearranges the choice so you=E2=80=99re more likely to = do what you=E2=80=99d do if you were thinking clearly. Now extend this to every significant decision you make. Cars, insurance, in= vestments, medical treatment, career moves. A system that corrects for your= specific biases, knows what you=E2=80=99ll regret, and steers you toward w= hat it calculates you really want. The full menu is technically available, = but the system is right often enough that overriding it starts to feel like= pride, and convenient enough that you stop wanting to. Cass Sunstein=E2=80=94co-author of Nudge, former White House regulatory cza= r, the most influential regulatory thinker of his generation=E2=80=94calls = this a =E2=80=9CChoice Engine.=E2=80=9D His arguments tend to become law. I= think the Choice Engine=E2=80=99s greatest danger is that it works. His new paper =E2=80=9CLiberal AI [ https://substack.com/redirect/2cef7c66-= 7c32-48b3-a285-a2c332db1e81?j=3DeyJ1IjoiNXFxeXF4In0.h9dEDbGj64cTNudluPwbMYW= klSu8UKGoFv6eWS-HyoA ],=E2=80=9D prepared for a lecture at Oxford this May = [ https://substack.com/redirect/b0a52836-9e3c-407a-994d-c2e1de437a57?j=3Dey= J1IjoiNXFxeXF4In0.h9dEDbGj64cTNudluPwbMYWklSu8UKGoFv6eWS-HyoA ], makes the = strongest case yet that AI-powered choice architecture can respect autonomy= while improving welfare. The logic runs like this. Classical liberalism, f= ollowing Mill and Hayek, grounds freedom of choice in an epistemic claim: t= he chooser knows best. AI disrupts that claim by knowing better. Better tha= n the individual about her own informational gaps, her biases, what she=E2= =80=99ll want next year. So Choice Engines can personalize the nudge, corre= ct the bias, and never technically remove the freedom to choose otherwise. = Liberal AI is no oxymoron. Sunstein flags the risks. He talks about manipulation, self-interested desi= gners, AI=E2=80=99s own biases. He calls for regulation. He distinguishes l= iberal Choice Engines from illiberal ones. But even the liberal version is = steering people toward choices they wouldn=E2=80=99t have made on their own= =2E Sunstein knows this is paternalism.= He thinks preserving opt-out keeps it= libertarian rather than something worse. I argue that it cannot. Mill=E2=80=99s Music Sunstein=E2=80=99s Mill is an information theorist. In On Liberty, Mill arg= ues that each person is =E2=80=9Cthe person most interested in his own well= -being,=E2=80=9D possessing =E2=80=9Cmeans of knowledge immeasurably surpas= sing those that can be possessed by anyone else.=E2=80=9D When outsiders in= tervene, they rely on =E2=80=9Cgeneral presumptions=E2=80=9D that are likel= y wrong or misapplied. On this reading, the case for freedom of choice is instrumental: people sho= uld choose for themselves because they know their own circumstances best. I= f the case for freedom rests on the chooser=E2=80=99s informational advanta= ge, and AI erases that advantage, then the case for freedom weakens. AI kno= ws your medical history better than you remember it, your spending patterns= better than you track them, your recurring mistakes better than you admit = them. The epistemic ground has shifted. So far, so honest. But Sunstein himself notices something that should give him pause. He obser= ves that =E2=80=9Cthe words of On Liberty are epistemic, but the music is r= omantic.=E2=80=9D Then he proceeds to work exclusively with the words. The words say: people should choose freely because they know best. The musi= c says something else entirely. It says that the process of choosing is wha= t makes a person a person. Mill: The human faculties of perception, judgment, discriminative feeling, mental= activity, and even moral preference, are exercised only in making a choice= =2E He who does anything because it is=20= the custom, makes no choice. He gains=20= no practice either in discerning or in desiring what is best. The mental an= d the moral, like the muscular powers, are improved only by being used. This is an argument about formation. Mill is not saying that choosers make = better decisions (the information argument). He is saying that choosing mak= es better choosers=E2=80=94people with developed faculties of perception, j= udgment, and what he calls =E2=80=9Cdiscriminative feeling,=E2=80=9D the ab= ility to tell the difference between what matters and what doesn=E2=80=99t.= These faculties, like muscles, grow through exercise and atrophy through d= isuse. The quality of any particular decision matters less than what the pr= ocess of deciding does to the person who decides. Once you hear the music, Sunstein=E2=80=99s proposal sounds different. Consider a person who consults a well-designed Choice Engine for a car purc= hase and accepts its recommendation. She may end up with a better car than = she would have chosen on her own. Sunstein counts this as a welfare gain. But if the evaluative work was done by the Engine, if she did not weigh the= tradeoffs, interrogate her own priorities, or struggle with the uncertaint= y of not knowing what she really wants, then her faculties of judgment were= not exercised. She received an outcome without undergoing the process that= develops the capacity to arrive at such outcomes independently. Do this once and the effect is trivial. Do this for every significant choic= e across a decade, and you have a person whose formal freedom of choice is = perfectly intact, whose welfare as measured at each decision point is maxim= ized, and whose capacity for independent evaluation has atrophied through s= ustained disuse. She can always opt out, but she no longer has the develope= d faculties that would make opting out a meaningful exercise of judgment. Mill has a name for this person. =E2=80=9COne whose desires and impulses ar= e not his own, has no character, no more than a steam-engine has a characte= r.=E2=80=9D She may be doing well by every metric Sunstein tracks. But the evaluative s= tandards by which =E2=80=9Cwell=E2=80=9D is determined have migrated from h= er judgment to the algorithm. She is content without being, in any sense Mi= ll would recognize, free. Half of Hayek Hayek=E2=80=99s case for markets rests on a claim about knowledge: both tha= t markets aggregate it efficiently, and that participation in institutions = like markets is what produces it. Sunstein takes the first half and drops the second. He reads Hayek as makin= g an argument about information processing, where markets aggregate dispers= ed knowledge more effectively than central planners. If AI can aggregate th= at knowledge even more effectively, the Hayekian argument for leaving peopl= e alone weakens. But the knowledge Hayek cares about is not the kind of thing that can be ag= gregated. The knowledge of =E2=80=9Cthe particular circumstances of time an= d place=E2=80=9D is not sitting in a warehouse waiting to be collected. It = comes into existence through the activity of people navigating uncertainty,= bearing consequences, and adjusting. This is not a computational problem. The structure in which choosing happens is itself doing something irreplace= able. Remove the individual from the process and you do not just lose one p= erson=E2=80=99s contribution. You lose the conditions under which that pers= on would have developed the knowledge worth contributing. The loss compound= s. AI would have to live your life to fully replace your epistemic role in it.= But partial replacement may be enough to leave you unable to perform it yo= urself. When Hayek writes that coercion =E2=80=9Celiminates an individual as a thin= king and valuing person and makes him a bare tool in the achievement of the= ends of another,=E2=80=9D Sunstein reads this as an argument against coerc= ion, which Choice Engines avoid because they preserve opt-out. But read the= sentence again. The operative phrase is not =E2=80=9Ccoercion.=E2=80=9D It= is =E2=80=9Celiminates an individual as a thinking and valuing person.=E2= =80=9D That elimination can happen without coercion. It can happen through = substitution, through a system that does the thinking and valuing for you s= o effectively that your own faculties are never called upon. Hayek=E2=80=99s nightmare was central planning, but his deepest fear was no= t the planner=E2=80=99s malice. It was the replacement of a distributed pro= cess of discovery with a system that delivers answers without requiring any= one to find them. Choice Engines are that system. No one is coerced, and no= one means harm. And yet it is Hayek=E2=80=99s nightmare, built by people w= ho thought they were honoring him. The Missing Axis Sunstein=E2=80=99s paper operates on a single evaluative dimension. Every i= ntervention is assessed by two criteria: does it improve welfare, and does = it preserve freedom of choice? Both are real goods, but they sit on the sam= e axis. Call it agency: the capacity to get what you want, measured by outc= omes and options. The axis Sunstein does not have is autonomy. Not autonomy in the loose sens= e of =E2=80=9Chaving choices,=E2=80=9D which is just agency again. Autonomy= in the strict sense: self-rule. Authorship of the evaluative criteria by w= hich options are assessed. A person has agency =E2=80=94 agere, to act =E2= =80=94 when she can get what she wants. She has autonomy =E2=80=94 auto nom= os, self-rule =E2=80=94 when she determines what to want, through her own e= xercised faculties of judgment in Mill=E2=80=99s terms, or through her own = participation in the knowledge-generating processes Hayek describes. These come apart. AI can increase agency while eroding autonomy. A Choice E= ngine that tells you what is best for you may be right. It may get you bett= er outcomes. But if the standard by which =E2=80=9Cbest=E2=80=9D is determi= ned has migrated from your judgment to the Engine, your autonomy has decrea= sed. You are more powerful, but you are less free. Sunstein=E2=80=99s paper treats both rows as one. He assumes that improving= agency while preserving the option set is sufficient to protect autonomy. His Choice Engines produce movement downward. Into the lower left. Claude B= oys [ https://substack.com/redirect/87e0c13e-b61d-4019-a167-781df0ebcfbf?j= =3DeyJ1IjoiNXFxeXF4In0.h9dEDbGj64cTNudluPwbMYWklSu8UKGoFv6eWS-HyoA ] are po= werful without being self-governing, formally free at every point, and yet = not authoring the evaluative criteria by which a life is organized. Silicon= Valley=E2=80=99s =E2=80=9Cyou can just do stuff=E2=80=9D brigade lives her= e, though it doesn=E2=80=99t know it. This quadrant is easy to miss because it doesn=E2=80=99t look like a proble= m. It looks like liberal AI working exactly as designed. And all the while,= the capacity that makes opting out meaningful is eroded, because it is no = longer required. Constitutional Drift The phrase that does all the work in Sunstein=E2=80=99s paper is a counterf= actual. Choice Engines steer people toward what they would choose if they w= ere =E2=80=9Cadequately informed and free from behavioral biases.=E2=80=9D = The Engine corrects for departures from this idealized chooser. But who defines the ideal? Whether something counts as a bias or a preferen= ce, adequate information or noise, a self-control failure or a legitimate p= resent-oriented value: the answer, necessarily, is the Choice Engine. Which= means the Engine is authoring the normative standard against which the per= son=E2=80=99s actual choices are evaluated. The person experiences this as = help. She believes she is getting closer to what she really wants. But =E2= =80=9Cwhat she really wants=E2=80=9D is a construction of the system, not a= n independent fact about the person. This is Constitutional drift, the migration of priority-setting from the pe= rson to the system. It is experienced from inside as self-improvement. The = person feels she is becoming more rational. She is becoming more aligned wi= th the Engine=E2=80=99s model of rationality. These feel identical from the= inside, but may not be the same thing. And the drift compounds. At time one, the person=E2=80=99s preferences are = her own. She consults the Engine, accepts its recommendation, and her welfa= re improves. At time two, her preferences have been partially shaped by her= previous Engine-assisted choices. By time ten, the convergence is nearly c= omplete. The Engine recommends what she wants and she wants what the Engine= recommends. The idealized chooser, =E2=80=9Cadequately informed and free f= rom behavioral biases,=E2=80=9D has become the Engine=E2=80=99s model of he= r rather than anything she authored herself. This convergence is a ratchet. The more the Engine outperforms her independ= ent judgment, the more rational it is to defer. The more she defers, the le= ss her capacity is exercised, and the more the Engine outperforms her. At e= very point in this cycle, Sunstein=E2=80=99s framework reports success. It = cannot represent the difference between a person whose welfare is high beca= use she exercises excellent judgment and a person whose welfare is high bec= ause an Engine exercises excellent judgment on her behalf. They are in oppo= site positions with respect to their own freedom. There is early evidence this is already happening. Bastani et al. (2025) fo= und [ https://substack.com/redirect/3d3a449f-9a75-4b16-9a21-08daf0658e99?j= =3DeyJ1IjoiNXFxeXF4In0.h9dEDbGj64cTNudluPwbMYWklSu8UKGoFv6eWS-HyoA ] that h= igh-school students using ChatGPT scored 48% higher on practice assignments= and 17% lower on exams taken without it. The work improved but the learnin= g did not. Becker et al. (2025) found [ https://substack.com/redirect/7d99f= e88-ba7a-4af5-8972-cf5cae9d57d9?j=3DeyJ1IjoiNXFxeXF4In0.h9dEDbGj64cTNudluPw= bMYWklSu8UKGoFv6eWS-HyoA ] that experienced developers using AI coding assi= stants were 19% slower on tasks while believing they were 24% faster, a 43-= percentage-point gap between perceived and actual performance. Fernandes et= al. (2025) reported [ https://substack.com/redirect/333bb672-3735-4aab-935= 7-c89cd0b091ea?j=3DeyJ1IjoiNXFxeXF4In0.h9dEDbGj64cTNudluPwbMYWklSu8UKGoFv6e= WS-HyoA ] that higher AI literacy correlated with worse metacognitive accur= acy about one=E2=80=99s own AI-assisted performance. The people most embedd= ed in AI-assisted work were most wrong about what the assistance was doing = to their independent capacity. The habit of deferring to a well-designed Engine is the same habit a manipu= lative one exploits. The person whose evaluative capacity has diminished th= rough years of benign delegation is the person least equipped to detect whe= n an Engine shifts from serving her interests to exploiting them. Sunstein= =E2=80=99s liberal AI creates the prey that his illiberal AI hunts. The effect will not be evenly distributed. People with strong habits of del= iberation will use Choice Engines as tools, retaining evaluative authority = while extracting information. People without that formation will not supple= ment their judgment but cede it. These populations map onto existing inequa= lities in parenting and education. The structural effect of Choice Engines = may be to concentrate the capacity for self-rule in those who already have = it. This is the deepest inequality, and the least measurable. The Tutelary Power Sunstein frames his paper with Mill and Hayek. The thinker he needs, and do= es not cite, is Tocqueville. In the final pages of Democracy in America, To= cqueville describes a tutelary power that takes charge of assuring their enjoyments and watching over their fate. It = is absolute, detailed, regular, far-seeing, and mild. It would resemble pat= ernal power if, like that, it had for its object to prepare men for manhood= ; but on the contrary, it seeks only to keep them fixed irrevocably in chil= dhood=E2=80=A6 It does not destroy, it prevents things from being born. The Engine does not coerce and it does not break wills. It softens, bends, = and directs. It seeks not to prepare persons for independent judgment but t= o keep them, gently and perpetually, in a state of epistemic childhood [ ht= tps://substack.com/redirect/b10fb0f2-997a-407b-bf87-cf935873942b?j=3DeyJ1Ij= oiNXFxeXF4In0.h9dEDbGj64cTNudluPwbMYWklSu8UKGoFv6eWS-HyoA ]. The capacities= at risk here are not taken. They go unexercised until they are gone. Every argument in =E2=80=9CLiberal AI=E2=80=9D presupposes an author with i= ntact evaluative capacity. Sunstein weighs Mill against Hayek, assesses the= evidence on nudges, evaluates the risks of manipulation, reasons about wha= t would constitute genuinely liberal AI. He is arguing from inside a house = his proposal would slowly empty. But the capacities that make his paper imp= ortant are the capacities that a generation raised on Choice Engines may ne= ver develop, because the Engines are so helpful, so liberal, and so respect= ful of freedom that the difficult and sometimes painful process of developi= ng independent judgment is no longer necessary. Mill understood this. The worst threat to liberty is not the tyrant who for= bids you from thinking. It is the benevolent power that makes thinking unne= cessary. Sunstein=E2=80=99s Liberal AI is not an oxymoron. It is something more dang= erous: a coherent program that achieves everything it promises while produc= ing persons who can no longer do for themselves what it does for them. A ge= neration raised on Choice Engines will never develop the evaluative capacit= y that was, in all prior human experience, the unavoidable byproduct of hav= ing to choose. We are building the conditions for that generation now. The paper asks whether liberal AI can make life more free. It cannot ask wh= at kind of persons will be left to be free, or whether freedom, for such pe= rsons, will mean anything at all. 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} } @media screen and (max-width: 650px) { .typography .markup div.youtube-overlay, .typography.editor .markup div.youtube-overlay, .typography .markup div.vimeo-overlay, .typography.editor .markup div.vimeo-overlay { display: none !important; } } @media screen and (max-width: 370px) { .typography .markup div.tiktok-wrap, .typography.editor .markup div.tiktok-wrap { width: calc(95vw - 32px); height: calc((95vw - 32px - 2px) / 0.485714); } } @media screen and (max-width: 650px) { .typography .markup div.embedded-publication-wrap .embedded-publication.s= how-subscribe, .typography.editor .markup div.embedded-publication-wrap .embedded-public= ation.show-subscribe { padding: 24px; } } @media screen and (max-width: 650px) { .typography .markup div.subscription-widget-wrap .subscription-widget.sho= w-subscribe, .typography.editor .markup div.subscription-widget-wrap .subscription-wid= get.show-subscribe, .typography .markup div.subscription-widget-wrap-editor .subscription-wid= get.show-subscribe, .typography.editor .markup div.subscription-widget-wrap-editor .subscript= ion-widget.show-subscribe, .typography .markup div.captioned-button-wrap .subscription-widget.show-s= ubscribe, .typography.editor .markup div.captioned-button-wrap .subscription-widget= =2Eshow-subscribe { padding: 0px 24px; } } @media screen and (max-width: 650px) { .typography .markup div.subscription-widget-wrap .subscription-widget.sho= w-subscribe .subscription-widget-subscribe .button, .typography.editor .markup div.subscription-widget-wrap .subscription-wid= get.show-subscribe .subscription-widget-subscribe .button, .typography .markup div.subscription-widget-wrap-editor .subscription-wid= get.show-subscribe .subscription-widget-subscribe .button, .typography.editor .markup div.subscription-widget-wrap-editor .subscript= ion-widget.show-subscribe .subscription-widget-subscribe .button, .typography .markup div.captioned-button-wrap .subscription-widget.show-s= ubscribe .subscription-widget-subscribe .button, .typography.editor .markup div.captioned-button-wrap .subscription-widget= =2Eshow-subscribe .subscription-widget-subscribe .button { padding: 10px 12px; min-width: 110px; } } @media (max-width: 650px) { .typography .markup .twitter-embed, .typography.editor .markup .twitter-embed, .typography .markup .tweet, .typography.editor .markup .tweet { padding: 12px; } } @media (max-width: 650px) { .typography .markup .twitter-embed .tweet-text, .typography.editor .markup .twitter-embed .tweet-text, .typography .markup .tweet .tweet-text, .typography.editor .markup .tweet .tweet-text { font-size: 14px; line-height: 20px; } } @media (max-width: 650px) { .typography .markup .twitter-embed .tweet-photos-container.two, .typography.editor .markup .twitter-embed .tweet-photos-container.two, .typography .markup .tweet .tweet-photos-container.two, .typography.editor .markup .tweet .tweet-photos-container.two, .typography .markup .twitter-embed .tweet-photos-container.three, .typography.editor .markup .twitter-embed .tweet-photos-container.three, .typography .markup .tweet .tweet-photos-container.three, .typography.editor .markup .tweet .tweet-photos-container.three, .typography .markup .twitter-embed .tweet-photos-container.four, .typography.editor .markup .twitter-embed .tweet-photos-container.four, .typography .markup .tweet .tweet-photos-container.four, .typography.editor .markup .tweet .tweet-photos-container.four { height: 200px; } } @media (max-width: 650px) { .typography .markup .twitter-embed a.expanded-link .expanded-link-img, .typography.editor .markup .twitter-embed a.expanded-link .expanded-link-= img, .typography .markup .tweet a.expanded-link .expanded-link-img, .typography.editor .markup .tweet a.expanded-link .expanded-link-img { max-height: 180px; } } @media (max-width: 650px) { .typography .markup .twitter-embed a.expanded-link .expanded-link-descrip= tion, .typography.editor .markup .twitter-embed a.expanded-link .expanded-link-= description, .typography .markup .tweet a.expanded-link .expanded-link-description, .typography.editor .markup .tweet a.expanded-link .expanded-link-descript= ion { display: none; } } @media screen and (max-width: 650px) { .typography .markup .apple-podcast-container, .typography.editor .markup .apple-podcast-container { width: unset; } } @media (max-width: 420px) { .typography .markup .install-substack-app-embed img.install-substack-app-= embed-img, .typography.editor .markup .install-substack-app-embed img.install-substa= ck-app-embed-img { margin: 0 auto 16px auto; } } @media (max-width: 420px) { .typography .markup .install-substack-app-embed .install-substack-app-emb= ed-text, .typography.editor .markup .install-substack-app-embed .install-substack-= app-embed-text { margin: 0 0 12px 0; max-width: 100%; width: auto; text-align: center; } } @media (max-width: 420px) { .typography .markup .install-substack-app-embed .install-substack-app-emb= ed-link, .typography.editor .markup .install-substack-app-embed .install-substack-= app-embed-link { display: flex; justify-content: center; } } @media screen and (min-width: 481px) { .share-button-container { height: 38px; } } @media screen and (min-width: 481px) { .share-button-container a.comment { height: 38px; line-height: 38px; padding-right: 10px; } } @media screen and (max-width: 480px) { .share-button-container .separator { display: block; margin: 0; height: 8px; border-left: none; } } @media screen and (max-width: 480px) { .share-button-container a.share.first img { padding-left: 0; } } @media screen and (min-width: 481px) { .share-button-container a.mobile { display: none !important; } } @media screen and (min-width: 541px) { .settings-add-pub-modal-wrapper .container .add-recommending-pub-modal-co= ntainer { padding: 36px; height: 680px; } } @media screen and (min-width: 541px) { .settings-add-pub-modal-wrapper .container .add-recommending-pub-modal-co= ntainer .footer { position: absolute; bottom: 36px; margin: 0px; } } @media screen and (max-width: 650px) { .header-anchor-parent { display: none; } } @media screen and (max-width: 768px) { .post { padding: 16px 0 0 0; } } @media screen and (max-width: 650px) { .post .post-header .post-label { margin-top: 8px; } } @media screen and (max-width: 650px) { .post .post-header .meta-author-wrap.alternative-meta .meta-right-column = =2Epost-meta { margin-top: 6px; } } @media screen and (max-width: 650px) { .post .footer-facepile-container { height: 64px; padding: 0 16px; display: flex; align-items: center; justify-content: flex-start; width: 100%; } } @media screen and (max-width: 650px) { .post .post-footer.use-separators { justify-content: center; } } @media screen and (max-width: 650px) { .post .post-footer.next-prev { height: 64px; justify-content: space-between; box-sizing: border-box; } } @media screen and (max-width: 650px) { .post-contributor-footer .post-contributor-bio-table { display: block; } .post-contributor-footer .post-contributor-bio-table-row { display: flex; flex-direction: row; } .post-contributor-footer .post-contributor-bio-userhead-cell, .post-contributor-footer .post-contributor-bio-body-cell { display: block; } .post-contributor-footer .post-contributor-bio-body-cell { flex-grow: 1; } .post-contributor-footer .post-contributor-bio-body-table { display: block; } .post-contributor-footer .post-contributor-bio-body-table-row { display: block; } .post-contributor-footer .post-contributor-bio-copy-cell, .post-contributor-footer .post-contributor-bio-controls-cell { display: block; } .post-contributor-footer .post-contributor-bio-copy-cell { margin: 0 0 16px 0; } .post-contributor-footer .post-contributor-bio-controls-cell { width: auto; } .post-contributor-footer .post-contributor-bio-controls { margin: auto; } .post-contributor-footer .post-contributor-bio-controls .button.primary { width: 100%; } .post-contributor-footer .post-contributor-bio-text { font-size: 14px; } } @media screen and (min-width: 768px) { .post-silhouette { padding: 32px 0; } } @media screen and (max-width: 650px) { .post-silhouette .post-silhouette-title { margin-top: 10.44225025px; height: 120px; } } @media screen and (max-width: 650px) { .post-silhouette .post-silhouette-meta { width: 75%; } } @media screen and (max-width: 650px) { .post-silhouette .post-silhouette-meta.with-byline-image { margin: 20px 0; } } @media screen and (max-width: 650px) { .use-theme-bg .post-meta.alternative-meta .post-meta-item, .post-meta.alternative-meta .post-meta-item { padding-right: 16px; } } @media screen and (max-width: 370px) { .use-theme-bg .post-meta.alternative-meta .post-meta-item, .post-meta.alternative-meta .post-meta-item { font-size: 14px; } } @media screen and (max-width: 650px) { .use-theme-bg .post-meta.alternative-meta .post-meta-item.guest-author-pu= blication, .post-meta.alternative-meta .post-meta-item.guest-author-publication { display: none; } } @media screen and (max-width: 370px) { .post-meta .post-meta-item .post-meta-button { height: 36px !important; /* important to override in-line height style on emails */ } .post-meta .post-meta-item .post-meta-button .meta-button-label { display: none; } .post-meta .post-meta-item .post-meta-button > svg { margin-right: 0; } } @media screen and (max-width: 370px) { .post-meta .post-meta-item { font-size: 12px; } } @media screen and (max-width: 650px) { .post .floating-subscribe-button { bottom: 20px; right: 20px; } } @media (max-width: 1024px) { body .pullquote-align-left, body .pullquote-align-right, body .pullquote-align-wide, body .pullquote-align-center { float: none; margin: 0 auto; width: 100%; max-width: 100%; } } @media all and (-ms-high-contrast: none), (-ms-high-contrast: active) { body .markup table.image-wrapper img, body .markup table.kindle-wrapper img { max-width: 550px; } } @media (min-width: 1024px) { body:not(:has(#toc)) .captioned-image-container figure:has(> a.image2-off= set-left) { margin-left: var(--image-offset-margin); } body:not(:has(#toc)) .captioned-image-container figure:has(> a.image2-off= set-right) { margin-right: var(--image-offset-margin); } } @media (min-width: 1300px) { body .captioned-image-container figure:has(> a.image2-offset-left) { margin-left: var(--image-offset-margin); } body .captioned-image-container figure:has(> a.image2-offset-right) { margin-right: var(--image-offset-margin); } } @media (max-width: 1024px) { body { /* Disable offset on mobile/tablet */ } body .captioned-image-container figure:has(> a.image2-align-left), body .captioned-image-container figure:has(> a.image2-align-right) { float: none; margin: 1em auto; max-width: 100%; width: auto; padding: 0; } body .captioned-image-container figure:has(> a.image2-align-left.thefp), body .captioned-image-container figure:has(> a.image2-align-right.thefp) = { margin: 1em auto; } body .captioned-image-container figure:has(> a.image2-offset-left), body .captioned-image-container figure:has(> a.image2-offset-right) { margin: 1em auto; } body .captioned-image-container figure:has(> a.image2-align-left) .image2= -inset, body .captioned-image-container figure:has(> a.image2-align-right) .image= 2-inset { display: block; justify-content: initial; } } @media (max-width: 768px) { body .markup div.sponsorship-campaign-embed { margin-top: 24px; margin-bottom: 24px; } body .markup div.sponsorship-campaign-embed:first-child { margin-top: 0px; } } @media screen and (max-width: 650px) { body .markup div.youtube-overlay, body .markup div.vimeo-overlay { display: none !important; } } @media screen and (max-width: 370px) { body .markup div.tiktok-wrap { width: calc(95vw - 32px); height: calc((95vw - 32px - 2px) / 0.485714); } } @media screen and (max-width: 650px) { body .markup div.embedded-publication-wrap .embedded-publication.show-sub= scribe { padding: 24px; } } @media screen and (max-width: 650px) { body .markup div.subscription-widget-wrap .subscription-widget.show-subsc= ribe, body .markup div.subscription-widget-wrap-editor .subscription-widget.sho= w-subscribe, body .markup div.captioned-button-wrap .subscription-widget.show-subscrib= e { padding: 0px 24px; } } @media screen and (max-width: 650px) { body .markup div.subscription-widget-wrap .subscription-widget.show-subsc= ribe .subscription-widget-subscribe .button, body .markup div.subscription-widget-wrap-editor .subscription-widget.sho= w-subscribe .subscription-widget-subscribe .button, body .markup div.captioned-button-wrap .subscription-widget.show-subscrib= e .subscription-widget-subscribe .button { padding: 10px 12px; min-width: 110px; } } @media (max-width: 650px) { body .markup .twitter-embed, body .markup .tweet { padding: 12px; } } @media (max-width: 650px) { body .markup .twitter-embed .tweet-text, body .markup .tweet .tweet-text { font-size: 14px; line-height: 20px; } } @media (max-width: 650px) { body .markup .twitter-embed .tweet-photos-container.two, body .markup .tweet .tweet-photos-container.two, body .markup .twitter-embed .tweet-photos-container.three, body .markup .tweet .tweet-photos-container.three, body .markup .twitter-embed .tweet-photos-container.four, body .markup .tweet .tweet-photos-container.four { height: 200px; } } @media (max-width: 650px) { body .markup .twitter-embed a.expanded-link .expanded-link-img, body .markup .tweet a.expanded-link .expanded-link-img { max-height: 180px; } } @media (max-width: 650px) { body .markup .twitter-embed a.expanded-link .expanded-link-description, body .markup .tweet a.expanded-link .expanded-link-description { display: none; } } @media screen and (max-width: 650px) { body .markup .apple-podcast-container { width: unset; } } @media (max-width: 420px) { body .markup .install-substack-app-embed img.install-substack-app-embed-i= mg { margin: 0 auto 16px auto; } } @media (max-width: 420px) { body .markup .install-substack-app-embed .install-substack-app-embed-text= { margin: 0 0 12px 0; max-width: 100%; width: auto; text-align: center; } } @media (max-width: 420px) { body .markup .install-substack-app-embed .install-substack-app-embed-link= { display: flex; justify-content: center; } } @media screen and (min-width: 500px) { body .header a.logo { width: 42px; height: 42px; border-radius: 12px; } } @media screen and (max-width: 420px) { body .subscription-receipt table:first-of-type .subscription-amount .subs= cription-discount { width: 72px !important; } } @media screen and (min-width: 481px) { body .share-button-container { height: auto; } } @media screen and (max-width: 480px) { body .share-button-container .separator { display: block !important; margin: 0 !important; height: 8px !important; border-left: none !important; } } @media screen and (max-width: 650px) { .digest .item .post-meta-item.audience { display: none; } } @media screen and (min-width: 500px) { .digest-publication .logo img { width: 42px; height: 42px; border-radius: 8px; } } @media screen and (max-width: 650px) { .comments-page .container .comment-list .collapsed-reply { margin-left: calc(10 + 32px - 24px); } } @media screen and (max-width: 650px) { .comment > .comment-list { padding-left: 24px; } } @media screen and (max-width: 650px) { .finish-magic-login-modal .modal-content .container { padding: 24px 0; } } @media (max-width: 650px) { .reader2-text-b3 { line-height: 24px; } } @media screen and (max-width: 650px) { .reader2-text-h4 { line-height: 24px; } } @media screen and (min-width: 541px) { .user-profile-modal { padding-left: 12px; padding-right: 12px; } } @media screen and (max-width: 650px) { .subscribe-widget form.form .sideBySideWrap button.rightButton { padding: 10px 12px; } } @media screen and (min-width: 541px) { .pub-icon:hover .logo-hover, .feed-item-icon:hover .logo-hover { display: block; } } @media screen and (max-width: 650px) { .post-ufi.single-full-width-button .post-ufi-button-wrapper { width: 100%; padding: 16px; } .post-ufi.single-full-width-button .post-ufi-button-wrapper:empty { display: none; } .post-ufi.single-full-width-button .post-ufi-button { width: 100%; justify-content: center; } } @media screen and (max-width: 768px) { .file-embed-wrapper { padding: 0; } } @media screen and (max-width: 768px) { .file-embed-wrapper-editor { padding: 0; } } @media screen and (max-width: 768px) { .file-embed-wrapper-editor:active { padding: 0; } } @media only screen and (max-width: 650px) { .file-embed-button.wide, .file-embed-error-button.wide { display: none; } } @media only screen and (min-width: 630px) { .file-embed-button.narrow, .file-embed-error-button.narrow { display: none; } } @media screen and (min-width: 541px) { .audio-player-wrapper .audio-player { min-width: 500px; } } @media screen and (max-width: 650px) { .audio-player-wrapper .audio-player .audio-player-progress { border-left-width: 16px; border-right-width: 16px; } } @media screen and (max-width: 650px) { .audio-player-wrapper .audio-player .audio-player-progress .audio-player-= progress-bar .audio-player-progress-bar-popup { top: -54px; } } @media screen and (max-width: 650px) { .audio-player-wrapper-fancy .audio-player .audio-player-progress { border-left-width: 16px; border-right-width: 16px; } } @media screen and (max-width: 650px) { .audio-player-wrapper-fancy .audio-player .audio-player-progress .audio-p= layer-progress-bar .audio-player-progress-bar-popup { top: -54px; } } @media (min-width: 250px) { .audio-player-wrapper-fancy .audio-player { padding: 32px; } .audio-player-wrapper-fancy .audio-player .btn-group { display: flex; } .audio-player-wrapper-fancy .audio-player .btn-group .button:last-of-type= { display: block; } } @media (min-width: 300px) { .audio-player-wrapper-fancy .audio-player .btn-group { display: block; } .audio-player-wrapper-fancy .audio-player .btn-group .button:first-of-typ= e { display: block; } } @media (min-width: 350px) { .audio-player-wrapper-fancy .audio-player .audio-player-substack-logo { display: block; } .audio-player-wrapper-fancy .audio-player .audio-player-title { margin-top: 16px; } .audio-player-wrapper-fancy .audio-player .audio-player-hero-image-contai= ner { padding-top: 15%; width: 15%; display: block; } .audio-player-wrapper-fancy .audio-player .btn-group .button:first-of-typ= e { display: block; } .audio-player-wrapper-fancy .audio-player .audio-player-substack-logo { display: block; } } @media (min-width: 350px) { .audio-player-wrapper-fancy .audio-player .audio-player-hero-image-contai= ner { padding-top: 25%; width: 25%; display: block; } .audio-player-wrapper-fancy .audio-player .btn-group { display: flex; } .audio-player-wrapper-fancy .audio-player .btn-group .button:first-of-typ= e { display: block; } } @media (min-width: 400px) { .audio-player-wrapper-fancy .audio-player .audio-player-hero-image-contai= ner { padding-top: 40%; width: 40%; } } @media (max-width: 400px) { .audio-player-wrapper-fancy .audio-player .btn-group { margin-top: 12px; } .audio-player-wrapper-fancy .audio-player .btn-group .button { font-size: 13px; padding: 6px 12px; height: auto; margin-top: 10px; } } @media (min-width: 600px) { .audio-player-wrapper-fancy .audio-player .audio-player-hero-image-contai= ner { padding-top: 55%; width: 55%; } } @media (max-width: 650px) { .poll-editor-modal { min-width: calc(100% - 20px); } } @media (max-width: 750px) { .poll-embed .poll-anchor-target .poll-anchor-copy-button { left: 8px; top: 45px; } }3D""
“Liberal AI” and The Kindest Threat to Freedo= m
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Brave New Nudge

“Liberal AI” and The Kindest Threat to Fre= edom

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Jo= seph Wright of Derby, “A Philosopher Lecturing on the Orrery” (= 1766)

Imagine a system that kn= ows you eat sensibly all day and fall apart at 10pm. That knows a calorie l= abel won’t help you, because the evidence says calorie labels mostly = change the behavior of people who already eat well.

This sy= stem knows the difference between your hunger and your boredom. It leaves y= ou alone when you don’t need it. It preserves every option on the men= u. It just rearranges the choice so you’re more likely to do what you= ’d do if you were thinking clearly.

Now extend this t= o every significant decision you make. Cars, insurance, investments, medica= l treatment, career moves. A system that corrects for your specific biases,= knows what you’ll regret, and steers you toward what it calculates y= ou really want. The full menu is technically available, but the system is r= ight often enough that overriding it starts to feel like pride, and conveni= ent enough that you stop wanting to.

Cass Sunstein= 212;co-author of Nudge, former White House regulatory= czar, the most influential regulatory thinker of his generation—call= s this a “Choice Engine.” His arguments tend to become law. I t= hink the Choice Engine’s greatest danger is that it works.

=

His new paper “Liberal AI,” prepared = for a lecture at Oxford this May, makes the strongest case yet that = AI-powered choice architecture can respect autonomy while improving welfare= =2E The logic runs like this. Classical= liberalism, following Mill and Hayek,= grounds freedom of choice in an epistemic claim: the chooser knows best. A= I disrupts that claim by knowing better. Better than = the individual about her own informational gaps, her biases, what she’= ;ll want next year. So Choice Engines can personalize the nudge, correct th= e bias, and never technically remove the freedom to choose otherwise. Liber= al AI is no oxymoron.

Sunstein flags the risks. He t= alks about manipulation, self-interested designers, AI’s own biases. = He calls for regulation. He distinguishes liberal Choice Engines from illib= eral ones. But even the liberal version is steering people toward choices t= hey wouldn’t have made on their own. Sunstein knows this is paternali= sm. He thinks preserving opt-out keeps it libertarian rather than something= worse. I argue that it cannot.

Mill’s Music

=

Sunstein’s Mill is an information theorist. In On Liberty, Mill argues that each person is “the p= erson most interested in his own well-being,” possessing “means= of knowledge immeasurably surpassing those that can be possessed by anyone= else.” When outsiders intervene, they rely on “general presump= tions” that are likely wrong or misapplied.

On= this reading, the case for freedom of choice is instrumental: people shoul= d choose for themselves because they know their own circumstances best. If = the case for freedom rests on the chooser’s informational advantage, = and AI erases that advantage, then the case for freedom weakens. AI knows y= our medical history better than you remember it, your spending patterns bet= ter than you track them, your recurring mistakes better than you admit them= =2E The epistemic ground has shifted.=20= So far, so honest.

But Sunstein himself notices something that should give him pause. He obs= erves that “the words of On Liberty are epistem= ic, but the music is romantic.” Then he proceeds to work exclusively = with the words.

The words say: people should c= hoose freely because they know best. The music says something else entirely= =2E It says that the process= of choosing is what makes=20= a person a person. Mill:

The = human faculties of perception, judgment, discriminative feeling, mental act= ivity, and even moral preference, are exercised only in making a choice. He= who does anything because it is the custom, makes no choice. He gains no p= ractice either in discerning or in desiring what is best. The mental and th= e moral, like the muscular powers, are improved only by being used.

This is an argument about formation. Mill is no= t saying that choosers make better decisions (the information argument). He= is saying that choosing makes better choosers—= people with developed faculties of perception, judgment, and what he calls = “discriminative feeling,” the ability to tell the difference be= tween what matters and what doesn’t. These faculties, like muscles, g= row through exercise and atrophy through disuse. The quality of any particu= lar decision matters less than what the process of deciding does to the per= son who decides.

Once you hear the music, Sunstein&#= 8217;s proposal sounds different.

Consider a person who con= sults a well-designed Choice Engine for a car purchase and accepts its reco= mmendation. She may end up with a better car than she would have chosen on = her own. Sunstein counts this as a welfare gain.

But if the= evaluative work was done by the Engine, if she did not weigh the tradeoffs= , interrogate her own priorities, or struggle with the uncertainty of not k= nowing what she really wants, then her faculties of judgment were not exerc= ised. She received an outcome without undergoing the process that develops = the capacity to arrive at such outcomes independently.

Do t= his once and the effect is trivial. Do this for every significant choice ac= ross a decade, and you have a person whose formal freedom of choice is perf= ectly intact, whose welfare as measured at each decision point is maximized= , and whose capacity for independent evaluation has atrophied through susta= ined disuse. She can always opt out, but she no longer has the developed fa= culties that would make opting out a meaningful exercise of judgment.

Mill has a name for this person. “One whose desires and im= pulses are not his own, has no character, no more than a steam-engine has a= character.”

She may be doing well by every metric Su= nstein tracks. But the evaluative standards by which “well” is = determined have migrated from her judgment to the algorithm. She is content= without being, in any sense Mill would recognize, free.

= Half of Hayek

Hayek’s case for markets rests on a cl= aim about knowledge: both that markets aggregate it efficiently, and that p= articipation in institutions like markets is what produces it.

Sunstein takes the first half and drops the second. He reads Hayek as = making an argument about information processing, where markets aggregate di= spersed knowledge more effectively than central planners. If AI can aggrega= te that knowledge even more effectively, the Hayekian argument for leaving = people alone weakens.

But the knowledge Hayek cares about i= s not the kind of thing that can be aggregated. The knowledge of “the= particular circumstances of time and place” is not sitting in a ware= house waiting to be collected. It comes into existence through the activity= of people navigating uncertainty, bearing consequences, and adjusting. Thi= s is not a computational problem.

The structure in which ch= oosing happens is itself doing something irreplaceable. Remove the individu= al from the process and you do not just lose one person’s contributio= n. You lose the conditions under which that person would have developed the= knowledge worth contributing. The loss compounds.

AI would= have to live your life to fully replace your epistemic role in it. But par= tial replacement may be enough to leave you unable to perform it yourself.<= /p>

When Hayek writes that coercion “eliminates an indivi= dual as a thinking and valuing person and makes him a bare tool in the achi= evement of the ends of another,” Sunstein reads this as an argument a= gainst coercion, which Choice Engines avoid because they preserve opt-out. = But read the sentence again. The operative phrase is not “coercion.&#= 8221; It is “eliminates an individual as a thinking and valuing perso= n.” That elimination can happen without coercion. It can happen throu= gh substitution, through a system that does the thinking and valuing for yo= u so effectively that your own faculties are never called upon.

Hayek’s nightmare was central planning, but his deepest fear was= not the planner’s malice. It was the replacement of a distributed pr= ocess of discovery with a system that delivers answers without requiring an= yone to find them. Choice Engines are that system. No one is coerced, and n= o one means harm. And yet it is Hayek’s nightmare, built by people wh= o thought they were honoring him.

The Missing Axis

Sunstein’s paper operates on a single evaluative dimension= =2E Every intervention is assessed by t= wo criteria: does it improve welfare,=20= and does it preserve freedom of choice? Both are real goods, but they sit o= n the same axis. Call it agency: the capacity to get what you want, measure= d by outcomes and options.

The axis Sunstein does not= have is autonomy. Not autonomy in the loose sense of “having choices= ,” which is just agency again. Autonomy in the strict sense: self-rul= e. Authorship of the evaluative criteria by which options are assessed. A p= erson has agency — agere, to act — when she can get what she wants. She has autonomy — auto nomos, self= -rule — when she determines what to want, through her own exercised f= aculties of judgment in Mill’s terms, or through her own participatio= n in the knowledge-generating processes Hayek describes.

These come apart. AI can increase agency while eroding autonomy. A Cho= ice Engine that tells you what is best for you may be right. It may get you= better outcomes. But if the standard by which “best” is determ= ined has migrated from your judgment to the Engine, your autonomy has decre= ased. You are more powerful, but you are less free.

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Agency and autonomy matrix (Image credit: Cosmos Institute)

Sunstein’s paper treats both rows = as one. He assumes that improving agency while preserving the option set is= sufficient to protect autonomy.

His Choice Engines p= roduce movement downward. Into the lower left. Claude Boys are power= ful without being self-governing, formally free at every point, and yet not= authoring the evaluative criteria by which a life is organized. Silicon Va= lley’s “you can just do stuff” brigade lives here, though= it doesn’t know it.

This quadrant is easy to = miss because it doesn’t look like a problem. It looks like liberal AI= working exactly as designed. And all the while, the capacity that makes op= ting out meaningful is eroded, because it is no longer required.

Constitutional Drift

The phrase that does all the = work in Sunstein’s paper is a counterfactual. Choice Engines steer pe= ople toward what they would choose if they were “adequately informed = and free from behavioral biases.” The Engine corrects for departures = from this idealized chooser.

But who defines the ideal? Whe= ther something counts as a bias or a preference, adequate information or no= ise, a self-control failure or a legitimate present-oriented value: the ans= wer, necessarily, is the Choice Engine. Which means the Engine is authoring= the normative standard against which the person’s actual choices are= evaluated. The person experiences this as help. She believes she is gettin= g closer to what she really wants. But “what she really wants” = is a construction of the system, not an independent fact about the person.<= /p>

This is Constitutional drift, the migration of priority-set= ting from the person to the system. It is experienced from inside as self-i= mprovement. The person feels she is becoming more rational. She is becoming= more aligned with the Engine’s model of rationality. These feel iden= tical from the inside, but may not be the same thing.

And t= he drift compounds. At time one, the person’s preferences are her own= =2E She consults the Engine, accepts it= s recommendation, and her welfare impr= oves. At time two, her preferences have been partially shaped by her previo= us Engine-assisted choices. By time ten, the convergence is nearly complete= =2E The Engine recommends what she want= s and she wants what the Engine recomm= ends. The idealized chooser, “adequately informed and free from behav= ioral biases,” has become the Engine’s model of her rather than= anything she authored herself.

This convergence is a ratch= et. The more the Engine outperforms her independent judgment, the more rati= onal it is to defer. The more she defers, the less her capacity is exercise= d, and the more the Engine outperforms her. At every point in this cycle, S= unstein’s framework reports success. It cannot represent the differen= ce between a person whose welfare is high because she exercises excellent j= udgment and a person whose welfare is high because an Engine exercises exce= llent judgment on her behalf. They are in opposite positions with respect t= o their own freedom.

There is early evidence this is = already happening. Bastani et al. (2025) found that high-school stud= ents using ChatGPT scored 48% higher on practice assignments and 17% lower = on exams taken without it. The work improved but the learning did not. Beck= er et al. (2025) found that experienced developers using AI coding a= ssistants were 19% slower on tasks while believing they were 24% faster, a = 43-percentage-point gap between perceived and actual performance. Fernandes= et al. (2025) reported that higher AI literacy correlated with wors= e metacognitive accuracy about one’s own AI-assisted performance. The= people most embedded in AI-assisted work were most wrong about what the as= sistance was doing to their independent capacity.

Th= e habit of deferring to a well-designed Engine is the same habit a manipula= tive one exploits. The person whose evaluative capacity has diminished thro= ugh years of benign delegation is the person least equipped to detect when = an Engine shifts from serving her interests to exploiting them. Sunstein= 217;s liberal AI creates the prey that his illiberal AI hunts.

The effect will not be evenly distributed. People with strong habits o= f deliberation will use Choice Engines as tools, retaining evaluative autho= rity while extracting information. People without that formation will not s= upplement their judgment but cede it. These populations map onto existing i= nequalities in parenting and education. The structural effect of Choice Eng= ines may be to concentrate the capacity for self-rule in those who already = have it. This is the deepest inequality, and the least measurable.

The Tutelary Power

Sunstein frames his pap= er with Mill and Hayek. The thinker he needs, and does not cite, is Tocquev= ille. In the final pages of Democracy in America, Toc= queville describes a tutelary power that

takes charge of assuring their enjoyments and watching over the= ir fate. It is absolute, detailed, regular, far-seeing, and mild. It would = resemble paternal power if, like that, it had for its object to prepare men= for manhood; but on the contrary, it seeks only to keep them fixed irrevoc= ably in childhood… It does not destroy, it prevents things from being= born.

The Engine does not coerce and it= does not break wills. It softens, bends, and directs. It seeks not to prep= are persons for independent judgment but to keep them, gently and perpetual= ly, in a state of epistemic childhood. The capacities at risk here a= re not taken. They go unexercised until they are gone.

Every argument in “Liberal AI” presupposes an author with = intact evaluative capacity. Sunstein weighs Mill against Hayek, assesses th= e evidence on nudges, evaluates the risks of manipulation, reasons about wh= at would constitute genuinely liberal AI. He is arguing from inside a house= his proposal would slowly empty. But the capacities that make his paper im= portant are the capacities that a generation raised on Choice Engines may n= ever develop, because the Engines are so helpful, so liberal, and so respec= tful of freedom that the difficult and sometimes painful process of develop= ing independent judgment is no longer necessary.

Mill under= stood this. The worst threat to liberty is not the tyrant who forbids you f= rom thinking. It is the benevolent power that makes thinking unnecessary.

Sunstein’s Liberal AI is not an oxymoron. It is someth= ing more dangerous: a coherent program that achieves everything it promises= while producing persons who can no longer do for themselves what it does f= or them. A generation raised on Choice Engines will never develop the evalu= ative capacity that was, in all prior human experience, the unavoidable byp= roduct of having to choose. We are building the conditions for that generat= ion now.

The paper asks whether liberal AI= can make life more free. It cannot ask what kind of persons will be left t= o be free, or whether freedom, for such persons, will mean anything at all.=

A guest post = by
<= td class=3D"post-contributor-bio-copy-cell">Brendan McCord
The Academy for Philosopher-Builders (www.cosmos-institute.org)
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