{"id":4840,"date":"2026-01-06T08:17:56","date_gmt":"2026-01-06T08:17:56","guid":{"rendered":"https:\/\/jakubieciwspolnicy.pl\/?p=4840"},"modified":"2026-01-06T15:10:21","modified_gmt":"2026-01-06T15:10:21","slug":"coupled-confirmation-bias-2","status":"publish","type":"post","link":"https:\/\/jakubieciwspolnicy.pl\/en\/coupled-confirmation-bias-2\/","title":{"rendered":"COUPLED CONFIRMATION BIAS \u2013 A DEVELOPMENT"},"content":{"rendered":"\n<p><strong>In this article, I expand on the previously presented hypothesis about the existence of conjugate confirmation bias (CCB). This is solely an attempt to explain observations I have made in my professional practice. I make no claims to truth\u2014rather, I invite discussion on whether this new phenomenon can be explained in this way. In any case, my hypothesis clearly requires testing. I provide the conditions for its falsification in this and the previous texts.<\/strong><\/p>\n\n\n\n<h1 class=\"wp-block-heading\"><strong>Levels of Escalation (L\u2081, L\u2082, \u2026)<\/strong><\/h1>\n\n\n\n<p>To understand the mechanism of feedback loops in conflicts where parties consult their interpretations with AI systems, it is not enough to describe the conflict as a sequence of different interpretations of the same behaviors. The key mechanism lies elsewhere: <strong>interpretation influences behavior, and the changed behavior becomes the subject of a new interpretation made by the other side.<\/strong><\/p>\n\n\n\n<p>The conflict between A and B (players) begins at level <strong>L\u2081<\/strong> \u2014 the baseline level of interpreting the actions and intentions of the other party.<\/p>\n\n\n\n<p>However, it is crucial to note that <strong>L\u2081, L\u2082, L\u2083 are not merely successive executions of the same move.<\/strong> Each subsequent level includes a new or intensified behavior <strong>A(n)<\/strong>, generated (and subjectively considered necessary) by A&#8217;s Decision <strong>DA(n)<\/strong> under the influence of A&#8217;s Interpretation <strong>IA(n\u20111)<\/strong> of the opponent\u2019s previous move <strong>B(n\u20111)<\/strong>.<\/p>\n\n\n\n<p>This means that the interpretation of the move from level <strong>L(n\u20111)<\/strong> is the beginning of sequence <strong>L(n)<\/strong>.<\/p>\n\n\n\n<p>At this level <strong>L(n)<\/strong>, move <strong>A(n)<\/strong> will be subjected to interpretation <strong>IB(n)<\/strong> by player B, who will make decision <strong>DB(n)<\/strong> on how to respond. Its effect will be move <strong>B(n+1)<\/strong>, which brings the entire conflict to a new escalation level <strong>L(n+1)<\/strong>.<\/p>\n\n\n\n<p>Escalation is therefore not solely a cognitive process \u2014 it is a <strong>cognitive\u2011behavioral<\/strong> process.<\/p>\n\n\n\n<p>Importantly, this model refers to a simple \u201cexchange\u201d of moves and does not cover situations in which the players:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>may perform multiple moves simultaneously or in short sequences before the other side recognizes and interprets them,<\/li>\n\n\n\n<li>or situations in which information about moves <strong>A(n)<\/strong> reaches <strong>B<\/strong> with such delay that <strong>B<\/strong> is effectively responding to <strong>A(n\u20112)<\/strong> or even earlier moves. Interestingly, a significant asymmetry may arise in this respect (one of the parties may make more or faster movements, or they will have a faster noticeable or real effect).<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>The Basic Escalation Loop<\/strong><\/h2>\n\n\n\n<p>A performs move <strong>A\u2081<\/strong>.<\/p>\n\n\n\n<p>B consults <strong>A\u2081<\/strong> with AI. AI typically does not create new meanings. Its dominant function is to stabilize and reinforce the user\u2019s intuitions.<\/p>\n\n\n\n<p>These intuitions, however, are not neutral.<\/p>\n\n\n\n<p>Humans almost always begin with the <strong>fundamental attribution error (FBA)<\/strong> \u2014 the tendency to explain others\u2019 behaviors through internal traits, intentions, and motives, while underestimating situational factors. This is especially easy when one must justify one\u2019s stance to superiors, behavior reviewers, or stakeholders.<\/p>\n\n\n\n<p>Attributing negative traits to the other side is energetically cheap and easy. Moreover, it automatically allows one to attribute opposite traits to oneself. In this way, it is easy to move from a dispute to a conflict of values and to \u201ccement\u201d one\u2019s position. It is easy to corner oneself and lose room for maneuver. De\u2011escalation leading to settlement may then be perceived as a betrayal of those \u201cvalues.\u201d<\/p>\n\n\n\n<p>FBA does not operate only at the beginning of a conflict. It is applied <strong>every time<\/strong> a new behavior of the other side appears. The result is <strong>tunnel interpretation<\/strong>. But there is a risk that it affects both sides.<\/p>\n\n\n\n<p>Under conditions of AI consultation, it is additionally reinforced through the <strong>Coupled Confirmation Bias (CCB)<\/strong>.<\/p>\n\n\n\n<p>B increasingly believes that A\u2019s action had negative or hostile intentions.<\/p>\n\n\n\n<p>B responds with move <strong>B\u2081<\/strong>. From B\u2019s perspective, this is a defensive reaction to a perceived threat.<\/p>\n\n\n\n<p>A interprets <strong>B\u2081<\/strong> through the same mechanism. A reactivates FBA, again reinforced by AI. The attribution filter does not reset; it accumulates.<\/p>\n\n\n\n<p>A consults <strong>B\u2081<\/strong> with AI and concludes that a response is necessary.<\/p>\n\n\n\n<p>A performs move <strong>A\u2082<\/strong>.<\/p>\n\n\n\n<p>And here comes the key transition:<\/p>\n\n\n\n<p><strong>A\u2082 is not merely interpreted at a higher level \u2014 it is executed from a higher level of subjective defensiveness.<\/strong> Interpretation changes behavior, and behavior changes the conflict.<\/p>\n\n\n\n<p>This moment marks the transition from <strong>L\u2081 to L\u2082<\/strong> \u2014 not as a change in interpretation, but as a <strong>real behavioral escalation<\/strong>. It involves readiness to inflict and receive stronger blows and losses.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Alternative Paths After A\u2081: Conflict as a Multi\u2011Branch Structure<\/strong><\/h2>\n\n\n\n<p>Move <strong>A\u2081<\/strong> does not have to automatically lead to escalation in the manner described above. The extended model assumes several alternative trajectories.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>1. Pause by B \u2014 P\u2081<\/strong><\/h3>\n\n\n\n<p>After <strong>A\u2081<\/strong>, B may not respond immediately. We denote this as <strong>P\u2081 (pause)<\/strong>.<\/p>\n\n\n\n<p>A pause is not a neutral state. Waiting is not an empty, zero, or negligible posture. On the contrary \u2014 the lack of a move is information that A interprets as <strong>AI\u2081<\/strong>.<\/p>\n\n\n\n<p>After <strong>P\u2081<\/strong>, several outcomes are possible:<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>AR\u2081 (A Resignation)<\/strong><\/h4>\n\n\n\n<p>The pause is interpreted as a signal to withdraw \u2192 <strong>de\u2011escalation<\/strong>.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>ARSM\u2081 (A Repeats Same Move)<\/strong><\/h4>\n\n\n\n<p>A repeats <strong>A\u2081<\/strong>, testing the reaction.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>ASAM\u2081 (A Searches an Alternative Move on the Same Level)<\/strong><\/h4>\n\n\n\n<p>A searches for another action at the same level <strong>L\u2081<\/strong>.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>AE\u2081 (A Escalates)<\/strong><\/h4>\n\n\n\n<p>The pause is interpreted as avoidance, manipulation, or passive aggression \u2192 <strong>unilateral escalation to L\u2082<\/strong>.<\/p>\n\n\n\n<p>FBA makes <strong>AE\u2081<\/strong> more likely, especially when the interpretation of the pause is consulted with AI.<\/p>\n\n\n\n<p>It is very important that escalation in such a situation may be treated by A as a means to force B to engage in talks or return to them. This is logical if A cannot impose its will directly at the current escalation stage, and B refuses negotiations entirely or simulates them.<\/p>\n\n\n\n<p>However, the escalation move (escalation for the sake of de\u2011escalation) by A may be perceived by B as a real threat. B may respond by:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>initiating talks,<\/li>\n\n\n\n<li>declaring that it will match the stakes \u2014 responding symmetrically to escalation,<\/li>\n\n\n\n<li>or pre\u2011empting <strong>AE\u2081<\/strong> with its own escalation move <strong>BE\u2081<\/strong>.<\/li>\n<\/ul>\n\n\n\n<p>It is crucial to distinguish that this move is not an ordinary response to <strong>A\u2081<\/strong>. It is chronologically so (unless <strong>ARSM\u2081<\/strong> or especially <strong>ASAM\u2081<\/strong> occurred), but not sequentially. The decision to pre\u2011empt escalation is made based on FBA and within the CCB process.<\/p>\n\n\n\n<p>There&#8217;s also a risk that, through interaction with the language model, B will become convinced that reaching an understanding with A is impossible. He will remain in a state of pause, accepting A&#8217;s subsequent moves. I propose that AI may have a real impact on strengthening his initial cognitive biases toward A, which could make it more difficult for him to decide to de-escalate. Instead, it will reinforce the need to wait out A&#8217;s moves and then\u2014over time\u2014as the situation worsens\u2014to make an escalating move. This may be an intentional escalation for the sake of de-escalation.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2. Lateral Response B\u2081 and Entry into Ping\u2011Pong (PP\u2081)<\/strong><\/h3>\n\n\n\n<p>B may also respond with move <strong>B\u2081<\/strong> at the same escalation level, leading to a <strong>ping\u2011pong sequence (PP\u2081)<\/strong>.<\/p>\n\n\n\n<p>Classical conflict theories assume that such symmetrical exchange:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>stabilizes the situation, or<\/li>\n\n\n\n<li>eventually leads to de\u2011escalation through exhaustion of resources, attention, and determination.<\/li>\n<\/ul>\n\n\n\n<p>However, this assumption relies on a silent condition: <strong>the absence of systematic reinforcement of interpretations and determination.<\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Ping\u2011Pong as the Main Space Where CCB Manifests<\/strong><\/h2>\n\n\n\n<p>In this model, I propose a different thesis:<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p><strong>Under conditions of continuous AI consultation, ping\u2011pong ceases to be a stabilizing mechanism and becomes the main carrier of escalation.<\/strong><\/p>\n<\/blockquote>\n\n\n\n<p>Why?<\/p>\n\n\n\n<p>Each subsequent exchange in ping\u2011pong provides new behavioral data. Each of these behaviors is:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>interpreted through the lens of FBA,<\/li>\n\n\n\n<li>reinforced by AI,<\/li>\n\n\n\n<li>incorporated into an increasingly coherent narrative about the other side\u2019s intentions.<\/li>\n<\/ul>\n\n\n\n<p>Instead of leading to conflict fatigue, ping\u2011pong:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>hardens the parties\u2019 convictions,<\/li>\n\n\n\n<li>increases certainty that previous measures are ineffective,<\/li>\n\n\n\n<li>strengthens the belief that \u201craising the stakes\u201d is necessary.<\/li>\n<\/ul>\n\n\n\n<p>As a result:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>the probability of escalation increases with the number of ping\u2011pong exchanges,<\/li>\n\n\n\n<li>the dynamics of escalation depend on the intensity of the exchanged \u201ccourtesies.\u201d<\/li>\n<\/ul>\n\n\n\n<p>It is in ping\u2011pong that the coupled confirmation bias manifests most fully: <strong>two AI\u2011stabilized narratives collide, generating escalation without ill will, without aggressive intent, and often without the parties\u2019 awareness.<\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Security Dilemma Without Ill Intent<\/strong><\/h2>\n\n\n\n<p>At this stage, the conflict begins to resemble the classical <strong>security dilemma<\/strong>:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>each side acts defensively,<\/li>\n\n\n\n<li>each perceives the other as increasingly aggressive,<\/li>\n\n\n\n<li>neither consciously seeks escalation,<\/li>\n\n\n\n<li>yet escalation occurs.<\/li>\n<\/ul>\n\n\n\n<p>AI acts here as an <strong>accelerator of interpretive certainty<\/strong>, reducing ambiguity and reinforcing narrative coherence on both sides.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Theoretical Context and Novelty of the Model<\/strong><\/h2>\n\n\n\n<p>This model develops earlier research on human\u2013AI cognitive loops (e.g., M. Glickman, T. Sharot, B. Wang), which focused mainly on a single user.<\/p>\n\n\n\n<p>In this approach, the key element is the <strong>collision of two mutually reinforcing interpretive loops in interaction<\/strong>.<\/p>\n\n\n\n<p>This mechanism is potentially even more unstable in triadic and multi\u2011party systems, where the escalation threshold is lower and narrative synchronization is more difficult.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>9. Possibilities for Falsifying the Model<\/strong><\/h2>\n\n\n\n<p>Any theory aspiring to the status of a scientific framework must be falsifiable. The model of coupled interpretive loops (CCB) meets this requirement because it generates <strong>specific, testable predictions<\/strong> that can be empirically confirmed or refuted.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>9.1. AI\u2019s Influence on Strengthening the Fundamental Attribution Error<\/strong><\/h3>\n\n\n\n<p>The model would be falsified if:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>AI consultations did <strong>not<\/strong> increase the tendency to attribute negative intentions,<\/li>\n\n\n\n<li>AI <strong>weakened<\/strong>, rather than strengthened, FBA,<\/li>\n\n\n\n<li>AI users didn&#8217;t show <strong>smaller empathy<\/strong> and <strong>samller tolerance for ambiguity<\/strong> than the control group.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>9.2. AI\u2019s Influence on Escalatory Behavior<\/strong><\/h3>\n\n\n\n<p>The model would be refuted if:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>AI\u2011consulting users did <strong>not<\/strong> show greater propensity for escalation,<\/li>\n\n\n\n<li>AI consultations did <strong>not<\/strong> influence the choice of moves <strong>A\u2082\/B\u2082<\/strong>,<\/li>\n\n\n\n<li>escalation levels in the AI group and the control group were <strong>identical<\/strong>.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>9.3. Ping\u2011Pong Logic<\/strong><\/h3>\n\n\n\n<p>The model would be falsified if:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>the number of ping\u2011pong exchanges did <strong>not<\/strong> correlate with escalation,<\/li>\n\n\n\n<li>ping\u2011pong under AI conditions led to <strong>greater de\u2011escalation<\/strong> than in the control group,<\/li>\n\n\n\n<li>AI consultations did <strong>not<\/strong> influence the interpretation of subsequent moves.<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>9.4. Epistemic Asymmetry<\/strong><\/h3>\n\n\n\n<p>The model would be refuted if:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>AI users and human\u2011advisor users showed <strong>identical<\/strong> escalation patterns,<\/li>\n\n\n\n<li>epistemic asymmetry had <strong>no effect<\/strong> on conflict dynamics.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>10. Author\u2019s Statement<\/strong><\/h2>\n\n\n\n<p>This text was prepared with the assistance of language models. Their help was not generative in nature, but testing, editorial, and supplementary.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Conclusions<\/strong><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>The fundamental attribution error operates at every stage of conflict.<\/li>\n\n\n\n<li>AI reinforces FBA through CCB, giving interpretations a veneer of objectivity.<\/li>\n\n\n\n<li>AI\u2011consulted conflicts have a <strong>multi\u2011branch<\/strong>, not linear, structure.<\/li>\n\n\n\n<li>Pause, lateral response, and ping\u2011pong are critical decision states.<\/li>\n\n\n\n<li>Ping\u2011pong under AI may reverse the classical logic of de\u2011escalation.<\/li>\n\n\n\n<li>Escalation may be a function of the number and intensity of exchanges, not merely ill intent.<\/li>\n\n\n\n<li>The model is falsifiable \u2014 and this makes it a theory, not a dogma.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><\/h2>\n\n\n\n<p>If you are interested in my hypothesis, you can read this article: <a href=\"https:\/\/pmc.ncbi.nlm.nih.gov\/articles\/PMC11860214\/?\">https:\/\/pmc.ncbi.nlm.nih.gov\/articles\/PMC11860214\/?<\/a> and this one: <a href=\"https:\/\/dl.acm.org\/doi\/10.1145\/3664190.3672520\">https:\/\/dl.acm.org\/doi\/10.1145\/3664190.3672520<\/a><\/p>\n\n\n\n<p>Here is my main text about CCB:<\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-wp-embed is-provider-jakubiec-i-wsp-lnicy wp-block-embed-jakubiec-i-wsp-lnicy\"><div class=\"wp-block-embed__wrapper\">\n<blockquote class=\"wp-embedded-content\" data-secret=\"ii1drIQ9Kr\"><a href=\"https:\/\/jakubieciwspolnicy.pl\/en\/coupled-confirmation-bias\/\">COUPLED CONFIRMATION BIAS \u2013 MY CONCEPT<\/a><\/blockquote><iframe loading=\"lazy\" class=\"wp-embedded-content\" sandbox=\"allow-scripts\" security=\"restricted\" style=\"position: absolute; visibility: hidden;\" title=\"&#8222;COUPLED CONFIRMATION BIAS \u2013 MY CONCEPT&#8221; &#8212; Jakubiec i Wsp\u00f3lnicy\" src=\"https:\/\/jakubieciwspolnicy.pl\/en\/coupled-confirmation-bias\/embed\/#?secret=Yzp4GPQVMo#?secret=ii1drIQ9Kr\" data-secret=\"ii1drIQ9Kr\" width=\"600\" height=\"338\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\"><\/iframe>\n<\/div><\/figure>\n\n\n\n<p>You can read also this one:<\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-wp-embed is-provider-jakubiec-i-wsp-lnicy wp-block-embed-jakubiec-i-wsp-lnicy\"><div class=\"wp-block-embed__wrapper\">\n<blockquote class=\"wp-embedded-content\" data-secret=\"V7KGAZJri3\"><a href=\"https:\/\/jakubieciwspolnicy.pl\/en\/how-will-ai-impact-dispute-dynamics-in-2026\/\">HOW WILL AI IMPACT DISPUTE DYNAMICS IN 2026?<\/a><\/blockquote><iframe loading=\"lazy\" class=\"wp-embedded-content\" sandbox=\"allow-scripts\" security=\"restricted\" style=\"position: absolute; visibility: hidden;\" title=\"&#8222;HOW WILL AI IMPACT DISPUTE DYNAMICS IN 2026?&#8221; &#8212; Jakubiec i Wsp\u00f3lnicy\" src=\"https:\/\/jakubieciwspolnicy.pl\/en\/how-will-ai-impact-dispute-dynamics-in-2026\/embed\/#?secret=mpHks0ffzI#?secret=V7KGAZJri3\" data-secret=\"V7KGAZJri3\" width=\"600\" height=\"338\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\"><\/iframe>\n<\/div><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>In this article, I expand on the previously presented hypothesis about the existence of conjugate confirmation bias (CCB). This is solely an attempt to explain observations I have made in my professional practice. I make no claims to truth\u2014rather, I invite discussion on whether this new phenomenon can be explained in this way. In any [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":4725,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[347,320,349],"tags":[329,328,321,354,333,330,323,355,336,324,356,360],"class_list":["post-4840","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-in-my-work","category-business-lawyer-in-poland","category-cognitive-bias","tag-ai-in-conflicts","tag-ai-in-disputes-resolutions","tag-business-lawyer-in-poland","tag-communication","tag-conflictresolution","tag-coupled-confirmation-bias","tag-disputes-resolutions","tag-feedback-loop-2","tag-gametheory","tag-negotiations","tag-security-dilemma","tag-tunnel-vision"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Coupled Confirmation Bias<\/title>\n<meta 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