{"id":1150522,"date":"2025-09-30T06:43:13","date_gmt":"2025-09-30T13:43:13","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-project&#038;p=1150522"},"modified":"2025-12-10T14:36:01","modified_gmt":"2025-12-10T22:36:01","slug":"digital-empathy-for-everyday-ai","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/digital-empathy-for-everyday-ai\/","title":{"rendered":"Digital Empathy for Everyday AI"},"content":{"rendered":"<section class=\"mb-3 moray-highlight\">\n\t<div class=\"card-img-overlay mx-lg-0\">\n\t\t<div class=\"card-background  has-background- card-background--full-bleed\">\n\t\t\t<img loading=\"lazy\" decoding=\"async\" width=\"1536\" height=\"1024\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/09\/6fb42350-d40f-47b7-a7df-8d8b083ccb9a.png\" class=\"attachment-full size-full\" alt=\"background pattern\" style=\"\" srcset=\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/09\/6fb42350-d40f-47b7-a7df-8d8b083ccb9a.png 1536w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/09\/6fb42350-d40f-47b7-a7df-8d8b083ccb9a-300x200.png 300w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/09\/6fb42350-d40f-47b7-a7df-8d8b083ccb9a-1024x683.png 1024w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/09\/6fb42350-d40f-47b7-a7df-8d8b083ccb9a-768x512.png 768w, https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2025\/09\/6fb42350-d40f-47b7-a7df-8d8b083ccb9a-240x160.png 240w\" sizes=\"auto, (max-width: 1536px) 100vw, 1536px\" \/>\t\t<\/div>\n\t\t<!-- Foreground -->\n\t\t<div class=\"card-foreground d-flex mt-md-n5 my-lg-5 px-g px-lg-0\">\n\t\t\t<!-- Container -->\n\t\t\t<div class=\"container d-flex mt-md-n5 my-lg-5 \">\n\t\t\t\t<!-- Card wrapper -->\n\t\t\t\t<div class=\"w-100 w-lg-col-5\">\n\t\t\t\t\t<!-- Card -->\n\t\t\t\t\t<div class=\"card material-md-card py-5 px-md-5\">\n\t\t\t\t\t\t<div class=\"card-body \">\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\n<h1 class=\"wp-block-heading\" id=\"digital-empathy-for-everyday-ai\">Digital Empathy for Everyday AI<\/h1>\n\n\n\n<p>Designing empathic interactions for helpful, human-centered AI<\/p>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/section>\n\n\n\n\n\n<p>As AI agents become woven into everyday life, from education and healthcare to customer support and productivity tools, we face a basic question. <strong>How should these systems understand and respond to us.<\/strong> We see digital empathy as an increasingly relevant idea driving the next wave of AI agent optimization. However, empathy is traditionally a human capacity that focuses on understanding and feeling another person\u2019s experience from within their frame of reference. In other words, the ability to place oneself in another person\u2019s position. Our project examines how AI systems can simulate parts of this capacity in ways that support, not replace, human understanding.<\/p>\n\n\n\n<p><strong>The promise is significant<\/strong>. In several studies, empathic strategies are associated with higher rapport and sustained engagement. In education and guided problem solving, affect sensitive systems report learning gains. In customer service, empathic approaches can raise satisfaction and intentions to return. <strong>The risks are real<\/strong>. Systems can misread signals or over personalize. People may worry about manipulation and consent. Privacy and transparency need active protection, and over time some users may become dependent on the system. When poorly executed, simulated empathy can also drift into sycophantic behavior that mirrors a user\u2019s preferences without demonstrating genuine understanding. Our response is practical. We pair empathic design with clear controls, simple opt in choices, plain language explanations, and careful evaluation so benefits grow while risks stay visible, measurable, and manageable.<\/p>\n\n\n\n<p>This goal of this effort is to bring clarity to a future where AI systems increasingly simulate empathy. We focus on defining digital empathy, mapping people\u2019s preferences, and identifying the contexts where it makes sense and where it does not. We create practical design patterns and safeguards for presenting empathic cues, test ways to promote beneficial uses, and examine broader implications for society, including equity, accountability, and shared norms. Our goal is a clear and actionable framework that helps teams build empathic AI that is measurable, transparent, and worthy of people\u2019s trust.<\/p>\n\n\n\n\n\n<p><\/p>\n\n\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Designing empathic interactions for helpful, human-centered AI As AI agents become woven into everyday life, from education and healthcare to customer support and productivity tools, we face a basic question. How should these systems understand and respond to us. We see digital empathy as an increasingly relevant idea driving the next wave of AI agent [&hellip;]<\/p>\n","protected":false},"featured_media":1150535,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"research-area":[13556,13554],"msr-locale":[268875],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-1150522","msr-project","type-msr-project","status-publish","has-post-thumbnail","hentry","msr-research-area-artificial-intelligence","msr-research-area-human-computer-interaction","msr-locale-en_us","msr-archive-status-active"],"msr_project_start":"","related-publications":[764092,799453,977535,1134749,1135076,1143217,1150394,1150396,1150400,1150407,1150415,1150418,1150625,1154986,1166807,1166860],"related-downloads":[],"related-videos":[],"related-groups":[1084857,1097541,1105932],"related-events":[],"related-opportunities":[],"related-posts":[],"related-articles":[],"tab-content":[],"slides":[],"related-researchers":[{"type":"user_nicename","display_name":"Judith Amores","user_id":42003,"people_section":"Related people","alias":"judithamores"},{"type":"user_nicename","display_name":"Javier Hernandez","user_id":38413,"people_section":"Related people","alias":"javierh"}],"msr_research_lab":[199563,199565],"msr_impact_theme":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/1150522","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-project"}],"version-history":[{"count":9,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/1150522\/revisions"}],"predecessor-version":[{"id":1150971,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/1150522\/revisions\/1150971"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/1150535"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=1150522"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=1150522"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=1150522"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=1150522"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=1150522"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}