{"id":11175,"date":"2024-06-27T11:00:00","date_gmt":"2024-06-27T09:00:00","guid":{"rendered":"https:\/\/escp.eu\/thechoice\/?p=11175"},"modified":"2024-06-28T16:37:00","modified_gmt":"2024-06-28T14:37:00","slug":"behind-the-algorithm-unveiling-trust-issues-in-ai-decisions","status":"publish","type":"post","link":"https:\/\/escp.eu\/thechoice\/tomorrow-choices\/behind-the-algorithm-unveiling-trust-issues-in-ai-decisions\/","title":{"rendered":"Behind the Algorithm: Unveiling Trust Issues in AI Decisions"},"content":{"rendered":"\n<p>In every situation, when there is a problem or an opportunity, someone must decide on several possible actions. In a business context, poor decision-making costs a firm, on average, at least<a href=\"https:\/\/hbr.org\/2023\/10\/how-ai-can-help-leaders-make-better-decisions-under-pressure#:~:text=In%20principle%2C%20generative%20AI%20systems,to%20making%20decisions%20under%20pressure.\" target=\"_blank\" rel=\"noreferrer noopener\"> 3% of profits<\/a>. Besides this financial loss, poor decision-making can affect other operational processes or customer satisfaction, significantly impacting companies&#8217; reputations.<\/p>\n\n\n\n<p>Therefore, <strong>good decision-making is crucial for a company<\/strong>. Of the ten most valuable companies,<a href=\"https:\/\/www.economist.com\/science-and-technology\/2018\/02\/17\/for-artificial-intelligence-to-thrive-it-must-explain-itself?ppccampaignID=&amp;ppcadID=&amp;ppcgclID=&amp;utm_medium=cpc.adword.pd&amp;utm_source=google&amp;ppccampaignID=18151738051&amp;ppcadID=&amp;utm_campaign=a.22brand_pmax&amp;utm_content=conversion.direct-response.anonymous&amp;gad_source=1&amp;gclid=EAIaIQobChMI6N_ehvjkhQMV8J9oCR2YPgC9EAAYAiAAEgLSMfD_BwE&amp;gclsrc=aw.ds\" target=\"_blank\" rel=\"noreferrer noopener\"> seven<\/a> are planning to put deep-learning-based AI at the heart of their operations. It signals the increasing importance of AI systems in organisational decision-making (<a href=\"https:\/\/www.mckinsey.com\/capabilities\/quantumblack\/our-%20insights\/the-state-of-ai-in-2023-generative-AIs-breakout-year\" target=\"_blank\" rel=\"noreferrer noopener\">33% of C-suite executives use GenAI in their work<\/a>), and a shared intent to invest in this technology (<a href=\"https:\/\/www.mckinsey.com\/capabilities\/quantumblack\/our-%20insights\/the-state-of-ai-in-2023-generative-AIs-breakout-year\" target=\"_blank\" rel=\"noreferrer noopener\">40% will increase their investment<\/a>).&nbsp;<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>It is crucial in today\u2019s world to consider and implement AI systems effectively to profit from their decision-making skills.<\/p>\n<\/blockquote>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>AI systems matter for decision-making<\/strong><\/h2>\n\n\n\n<p>The relevance of AI systems can be explained by rapid digitalisation and increasing demand to handle thousands of decisions every day. The decision-making processes that deal with the customer, a product or the supply chain cannot be handled manually anymore and go far beyond the capabilities of humans. While AI systems employ similar tools as organisational decision-making processes such as<a href=\"https:\/\/www.economist.com\/open-future\/2018\/11\/26\/ai-thinks-like-a-corporation-and-thats-worrying?utm_medium=cpc.adword.pd&amp;utm_source=google&amp;ppccampaignID=18151738051&amp;ppcadID=&amp;utm_campaign=a.22brand_pmax&amp;utm_content=conversion.direct-response.anonymous&amp;gad_source=1&amp;gclid=EAIaIQobChMI-c7jj_7khQMVpZiDBx12uAP9EAAYASAAEgL4tPD_BwE&amp;gclsrc=aw.ds\" target=\"_blank\" rel=\"noreferrer noopener\"> hierarchies of pre-set but adaptable rules<\/a> and draw<a href=\"https:\/\/www.economist.com\/science-and-technology\/2018\/02\/17\/for-artificial-intelligence-to-thrive-it-must-explain-itself?ppccampaignID=&amp;ppcadID=&amp;ppcgclID=&amp;utm_medium=cpc.adword.pd&amp;utm_source=google&amp;ppccampaignID=18151738051&amp;ppcadID=&amp;utm_campaign=a.22brand_pmax&amp;utm_content=conversion.direct-response.anonymous&amp;gad_source=1&amp;gclid=EAIaIQobChMI7JTx__3khQMVzaSDBx3fZgQ0EAAYAiAAEgKdO_D_BwE&amp;gclsrc=aw.ds\" target=\"_blank\" rel=\"noreferrer noopener\"> inspiration from the brain\u2019s neural network<\/a> to analyse and react to complex situations, <strong>AI systems stand out for their ability to handle tasks with more complexity, speed and scalability, leading to<\/strong><a href=\"https:\/\/hbr.org\/2021\/02\/when-should-you-use-ai-to-solve-problems\" target=\"_blank\" rel=\"noreferrer noopener\"><strong> better results<\/strong><\/a><strong>.<\/strong> Consequently, it is crucial in today\u2019s world to consider and implement AI systems effectively to profit from their decision-making skills.<\/p>\n\n\n\n<p>However, it is relevant to point out the potential negative side effects of AI systems. Besides the replication of biases from training data, leading to<a href=\"https:\/\/hbsp.harvard.edu\/product\/H06ORA-PDF-ENG\" target=\"_blank\" rel=\"noreferrer noopener\"> unfairness and discrimination<\/a>, disadvantages occur from the collaboration between humans and AI systems. AI systems<a href=\"https:\/\/www.pnas.org\/doi\/10.1073\/pnas.2307804120\" target=\"_blank\" rel=\"noreferrer noopener\"> replace humans&#8217; social coordination<\/a>, <a href=\"https:\/\/www.pnas.org\/doi\/10.1073\/pnas.2307804120\" target=\"_blank\" rel=\"noreferrer noopener\">enhancing unethical and self-interested behaviour, and inhibiting reciprocity between people<\/a>. In addition, humans misuse the tools due to<a href=\"https:\/\/www.economist.com\/science-and-technology\/2018\/02\/17\/for-artificial-intelligence-to-thrive-it-must-explain-itself?ppccampaignID=&amp;ppcadID=&amp;ppcgclID=&amp;utm_medium=cpc.adword.pd&amp;utm_source=google&amp;ppccampaignID=18151738051&amp;ppcadID=&amp;utm_campaign=a.22brand_pmax&amp;utm_content=conversion.direct-response.anonymous&amp;gad_source=1&amp;gclid=EAIaIQobChMI6N_ehvjkhQMV8J9oCR2YPgC9EAAYAiAAEgLSMfD_BwE&amp;gclsrc=aw.ds\" target=\"_blank\" rel=\"noreferrer noopener\"> incomprehensibility and a lack of transparency<\/a>. This fosters<a href=\"https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S0267364920300947?via%3Dihub\" target=\"_blank\" rel=\"noreferrer noopener\"> trust issues<\/a> in human-machine collaboration resulting in a preference for human judgements and a lack of consideration of AI suggestions.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>The ambiguity of trust in AI systems<\/strong><\/h2>\n\n\n\n<p>This preference for human judgements manifests as a<a href=\"https:\/\/dl.acm.org\/doi\/10.1145\/3334480.3382892\" target=\"_blank\" rel=\"noreferrer noopener\"> mistrust in AI systems<\/a>\u2019 capabilities while AI systems themselves tend to be <a href=\"https:\/\/journals.sagepub.com\/doi\/10.1177\/0261927X231220404\" target=\"_blank\" rel=\"noreferrer noopener\">more truth-biased than humans<\/a>. This <strong>trust ambiguity is explained by <\/strong><a href=\"https:\/\/journals.sagepub.com\/doi\/10.1177\/1064804618818592\" target=\"_blank\" rel=\"noreferrer noopener\"><strong>the nature of AI systems\u2019 <\/strong><\/a><strong>to be influenced by user characteristics, system design, and human experience with AI systems<\/strong>. Different perceptions of the material (text, picture, voice, etc.) created in specific situations will lower or increase the trust levels of humans in AI systems\u2019 work and decisions.<\/p>\n\n\n\n<p>When specifically referring to managerial decision-making, there is still a lack of knowledge in this field. Therefore, a recent study conducted by myself and classmates aimed to understand the level of trust humans have in AI systems in business. The goal was to understand the practical implications of AI integration into decision-making processes and test factors (Deception, Harmfulness, Confidence, and Integrity) that influence trust and dependency on AI systems in various business situations.&nbsp;<\/p>\n\n\n\n<p>Our research results have strengthened the ambiguity, presenting a variance in the variable outcomes. <strong>Participants do not significantly change their perception of Deception and Harmfulness; however, they do in terms of Confidence and Integrity.<\/strong> Therefore, decisions made by AI systems are surprisingly less trustworthy than those made by an expert.<\/p>\n\n\n\n<p>This highlights the importance of collaboration (human-machine) instead of replacement in a managerial context. Due to humans&#8217; intuitive judgement and ability to manage biases, they can surpass, to some extent, the capabilities of AI and therefore still play a vital role in decision-making processes.<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>Due to humans&#8217; intuitive judgement and ability to manage biases, they can surpass, to some extent, the capabilities of AI and therefore still play a vital role in decision-making processes.<\/p>\n<\/blockquote>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Be aware of mistrust<\/strong><\/h2>\n\n\n\n<p>Companies need to be aware of these trust issues. Our findings show that people trust AI systems less and therefore undervalue their decisions in a business context. However, AI-made decisions have significant advantages in speed, quality, and depth. Thus, companies need to communicate these concerns as well as the advantages to find the right balance. Compared to the average age of our participant group (20-30 years old), older generations commonly represented in companies might trust AI systems even less, leading to bad decision-making and financial and reputational loss.&nbsp;<\/p>\n\n\n\n<p><strong>It is the manager\u2019s role to act to understand and optimise the perception of trust in AI decision-making<\/strong>. They must clarify their objectives regarding trust in AI decision-making, observe and identify the levels of trust of their employees towards AI as a decision-maker and identify areas of improvement.<\/p>\n\n\n\n<p>We suggest these three key steps to understand and change trust perception in AI decision-making:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Objectives<\/strong>: Clarify objectives regarding Trust in AI decision-making<\/li>\n\n\n\n<li><strong>Observation<\/strong>: Identify the level of trust of employees towards AI as a decision-maker<\/li>\n\n\n\n<li><strong>Implication<\/strong>: Make improvements as necessary<\/li>\n<\/ol>\n\n\n\n<p>Following these steps can help to ensure a smoother integration of AI into businesses.<\/p>\n\n\n\n<p><\/p>\n\n\n\n<p><em>This article is based on a research project conducted by ESCP Business School Master in Management students Matteo Girelli, Suchet Kamble, Henrik Rippert, Alexander Schmachtenberg and Julius von Diergardt as part of the \u2018Shaping the Future of Leadership in the Digital Era\u2019 course of the \u2018Digital Transformation\u2019 specialisation, in collaboration with the <a href=\"https:\/\/escp.eu\/faculty-research\/chairs-professorships\/reinventing-work-chair\" target=\"_blank\" rel=\"noreferrer noopener\">Reinventing Work Chair<\/a> supported by BivwAk! BNP Paribas.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>ESCP Master in Management student Julius von Diergardt discusses the gaps in trust towards AI in business and how we might alleviate them.<\/p>\n","protected":false},"author":1,"featured_media":11174,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[14],"tags":[126,25,42,16],"class_list":["post-11175","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tomorrow-choices","tag-artificial-intelligence","tag-future-of-work","tag-leadership","tag-strategy","category-14","description-off"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Behind the Algorithm: Unveiling Trust Issues in AI Decisions - The Choice by ESCP<\/title>\n<meta name=\"description\" content=\"ESCP student 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