{ "@context": "https://schema.org", "@type": "ScholarlyArticle", "@id": "https://seanrintel.com/publications/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines.html#paper", "aboutThisFile": { "whatThisIs": "A research brief: a structured summary of one paper, prepared for seanrintel.com from the paper's full text.", "howItWasMade": "This brief was prepared with AI assistance and published by Sean Rintel. It is not the authors' published text.", "whatIsVerbatim": "Only 'quote' fields, figure captions and 'abstract' are the authors' own words. Research questions follow the paper's wording where it states them. Takeaway, summaries, answers, definitions and method are the site's plain-language paraphrase.", "howItIsChecked": "Before publication every quote is matched against the paper and every number in the brief is found in it. 'verified' is the date of the last check.", "howToUse": [ "For a quick answer, use 'takeaway' and 'questions'. For evidence, use 'findings' (each has a verbatim quote, its location in the paper and a 'url' anchored to that finding on the paper's page).", "Locations such as '§5.2, p. 9' refer to the version at 'pageNumbersReferTo'.", "For anything not covered here, read the paper itself: 'fullTextSources' lists free versions first.", "If 'researchOverview' is present, the paper is part of one of Sean Rintel's research overviews: it gives the overview's thesis, the claims this paper is evidence for and its role in each, and the other papers in the overview.", "To find other papers by Sean Rintel, use the catalogue at https://seanrintel.com/publications/index.json." ], "authorship": "Sean Rintel's role on each paper: lead author when he is first author, sole author when he is the only author, and otherwise senior author. Senior author here means the senior researcher on the team, whatever his position in the author list.", "howToCite": "Cite the paper, not this file: use 'citation' or the ready-made 'bibtex' (DOI where given) and name every author. Attribute paraphrase to the paper's findings, and use quotation marks only for 'quote' text." }, "name": "Meeting in the Middle: The Interpretation Gap Between People and Machines", "author": [ { "@type": "Person", "name": "Anastasia Kuzminykh" }, { "@type": "Person", "@id": "https://seanrintel.com/#sean-rintel", "name": "Sean Rintel", "url": "https://seanrintel.com/", "sameAs": [ "https://orcid.org/0000-0003-0840-0546", "https://scholar.google.com/citations?user=xc25GRgAAAAJ", "https://www.wikidata.org/wiki/Q102369654", "https://www.microsoft.com/en-us/research/people/serintel/", "https://www.linkedin.com/in/seanrintel" ] } ], "datePublished": "2019-05", "url": "https://seanrintel.com/publications/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines.html", "citation": "Anastasia Kuzminykh and Sean Rintel. 2019. Meeting in the Middle: The Interpretation Gap Between People and Machines. CHI 2019.", "bibtex": "@inproceedings{kuzminykh2019meeting,\nauthor = {Kuzminykh, Anastasia and Rintel, Sean},\ntitle = {Meeting in the Middle: The Interpretation Gap Between People and Machines},\norganization = {ACM},\nbooktitle = {CHI 2019},\nyear = {2019},\nmonth = {May},\nurl = {https://seanrintel.com/publications/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines.html},\nnote = {CHI 2019 Workshop on Where is the Human? Bridging the Gap Between AI and HCI},\n}", "abstract": "Effectively bridging the fields of HCI and AI requires operationalizing what human users treat as meaningful in the stream of environmental and content information. Research has yet to systematically address the significant gap between levels of granularity and interpretation of machine labels and of human comprehension. To illustrate the problem, we provide some preliminary results from our study on using machine vision to make work meetings more inclusive, particularly for visually impaired participants.", "fullTextSources": [ { "kind": "freeAccess", "url": "https://seanrintel.com/publications/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines.pdf", "label": "Author's Copy" } ], "fullTextAvailable": true, "takeaway": "Machines describing meetings to visually impaired colleagues must bridge an interpretation gap. A cue people call simple and objective, like someone 'listening to both of them', is many pose and gaze labels added up. That is because social attention is selective sense-making, not just what can be seen.", "researchOverview": { "name": "Better Thinking With AI", "page": "https://seanrintel.com/better-thinking-with-ai.html", "json": "https://seanrintel.com/overviews/better-thinking-with-ai.json", "markdown": "https://seanrintel.com/overviews/better-thinking-with-ai.md", "thesis": "Generative AI moves people's thinking into stating what they want and judging what they get. The easiest way to use it can help least, so good tools ask people to think first.", "claimsThisPaperFeeds": [ { "claim": "Asking for goals before AI drafts can improve the work", "role": "supporting evidence", "url": "https://seanrintel.com/better-thinking-with-ai.html#a6" } ], "otherPapers": [ { "study": "Review: productivity loss with AI", "title": "Ironies of Generative AI: Understanding and Mitigating Productivity Loss in Human-AI Interaction", "page": "https://seanrintel.com/publications/ironies-of-generative-ai-understanding-and-mitigating-productivity-loss-in-human-ai-interaction.html", "researchBrief": "https://seanrintel.com/publications/ironies-of-generative-ai-understanding-and-mitigating-productivity-loss-in-human-ai-interaction.json" }, { "study": "Survey: critical thinking at work", "title": "The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers", "page": "https://seanrintel.com/publications/the-impact-of-generative-ai-on-critical-thinking-self-reported-reductions-in-cognitive-effort-and-confidence-effects-from-a-survey-of-knowledge-workers.html", "researchBrief": "https://seanrintel.com/publications/the-impact-of-generative-ai-on-critical-thinking-self-reported-reductions-in-cognitive-effort-and-confidence-effects-from-a-survey-of-knowledge-workers.json" }, { "study": "Position paper: what skill at work means", "title": "The Future of Skill: What Is It to Be Skilled at Work?", "page": "https://seanrintel.com/publications/the-future-of-skill-what-is-it-to-be-skilled-at-work.html", "researchBrief": "https://seanrintel.com/publications/the-future-of-skill-what-is-it-to-be-skilled-at-work.json" }, { "study": "Conceptual analysis: metacognition and AI", "title": "The Metacognitive Demands and Opportunities of Generative AI", "page": "https://seanrintel.com/publications/the-metacognitive-demands-and-opportunities-of-generative-ai.html", "researchBrief": "https://seanrintel.com/publications/the-metacognitive-demands-and-opportunities-of-generative-ai.json" }, { "study": "Prompting study: AI-assisted data analysis", "title": "“It’s like a rubber duck that talks back”: Understanding Generative AI-Assisted Data Analysis Workflows through a Participatory Prompting Study", "page": "https://seanrintel.com/publications/its-like-a-rubber-duck-that-talks-back-understanding-generative-ai-assisted-data-analysis-workflows-through-a-participatory-prompting-study.html", "researchBrief": "https://seanrintel.com/publications/its-like-a-rubber-duck-that-talks-back-understanding-generative-ai-assisted-data-analysis-workflows-through-a-participatory-prompting-study.json" }, { "study": "Method paper: participatory prompting", "title": "Participatory prompting: a user-centric research method for eliciting AI assistance opportunities in knowledge workflows", "page": "https://seanrintel.com/publications/participatory-prompting-a-user-centric-research-method-for-eliciting-ai-assistance-opportunities-in-knowledge-workflows.html", "researchBrief": "https://seanrintel.com/publications/participatory-prompting-a-user-centric-research-method-for-eliciting-ai-assistance-opportunities-in-knowledge-workflows.json" }, { "study": "Commentary: role-based prompts", "title": "Productivity implications for generative AI role-based prompts as a networked hermeneutic (Commentary)", "page": "https://seanrintel.com/publications/productivity-implications-for-generative-ai-role-based-prompts-as-a-networked-hermeneutic.html", "researchBrief": "https://seanrintel.com/publications/productivity-implications-for-generative-ai-role-based-prompts-as-a-networked-hermeneutic.json" }, { "study": "Randomised trial: how students learn with AI", "title": "Learning behavior accounts for background-related advantage in AI-assisted education", "page": "https://seanrintel.com/publications/learning-behavior-accounts-for-background-related-advantage-in-ai-assisted-education.html", "researchBrief": "https://seanrintel.com/publications/learning-behavior-accounts-for-background-related-advantage-in-ai-assisted-education.json" }, { "study": "Randomised experiment: note-taking versus AI for reading", "title": "Effects of LLM Use and Note-Taking On Reading Comprehension and Memory: A Randomised Experiment in Secondary Schools", "page": "https://seanrintel.com/publications/effects-of-llm-use-and-note-taking-on-reading-comprehension-and-memory-a-randomised-experiment-in-secondary-schools.html", "researchBrief": "https://seanrintel.com/publications/effects-of-llm-use-and-note-taking-on-reading-comprehension-and-memory-a-randomised-experiment-in-secondary-schools.json" }, { "study": "Interviews: AI in higher education", "title": "The New Calculator? Practices, Norms, and Implications of Generative AI in Higher Education", "page": "https://seanrintel.com/publications/the-new-calculator-practices-norms-and-implications-of-generative-ai-in-higher-education.html", "researchBrief": "https://seanrintel.com/publications/the-new-calculator-practices-norms-and-implications-of-generative-ai-in-higher-education.json" }, { "study": "Randomised experiment: scaffolds for AI-assisted writing", "title": "Metacognitive Scaffolds Create Productive Friction for AI-Assisted Knowledge Work", "page": "https://seanrintel.com/publications/metacognitive-scaffolds-create-productive-friction-for-ai-assisted-knowledge-work.html", "researchBrief": "https://seanrintel.com/publications/metacognitive-scaffolds-create-productive-friction-for-ai-assisted-knowledge-work.json" }, { "study": "Lab study: prompt refinement controls", "title": "Dynamic Prompt Middleware: Contextual Prompt Refinement Controls for Comprehension Tasks", "page": "https://seanrintel.com/publications/dynamic-prompt-middleware-contextual-prompt-refinement-controls-for-comprehension-tasks.html", "researchBrief": "https://seanrintel.com/publications/dynamic-prompt-middleware-contextual-prompt-refinement-controls-for-comprehension-tasks.json" }, { "study": "Workshop proposal: AI as a tool for thought", "title": "Tools for Thought: Understanding, Protecting, and Augmenting Human Cognition with Generative AI — From Vision to Implementation", "page": "https://seanrintel.com/publications/tools-for-thought-understanding-protecting-and-augmenting-human-cognition-with-generative-ai-from-vision-to-implementation.html", "researchBrief": "https://seanrintel.com/publications/tools-for-thought-understanding-protecting-and-augmenting-human-cognition-with-generative-ai-from-vision-to-implementation.json" }, { "study": "System design: AI agents for diverse ideas", "title": "YES AND: A Generative AI Multi-Agent Framework for Enhancing Diversity of Thought in Individual Ideation for Problem-Solving Through Confidence-Based Agent Turn-Taking", "page": "https://seanrintel.com/publications/yes-and-a-generative-ai-multi-agent-framework-for-enhancing-diversity-of-thought-in-individual-ideation-for-problem-solving-through-confidence-based-agent-turn-taking.html", "researchBrief": "https://seanrintel.com/publications/yes-and-a-generative-ai-multi-agent-framework-for-enhancing-diversity-of-thought-in-individual-ideation-for-problem-solving-through-confidence-based-agent-turn-taking.json" } ] }, "whyItMatters": { "stateOfTheArt": { "summary": "Machine vision can already label basic visual information such as pose and gaze.", "quote": "Research has yet to systematically address the significant gap between levels of granularity and interpretation of machine labels and of human comprehension.", "location": "Abstract, p. 1" }, "contribution": { "summary": "Preliminary results from interviews with visually impaired employees and a narration study, yielding a structural model of how people describe social attention in meetings.", "quote": "the output viewed by human users as elemental and objective is, in fact, often highly interpretive and requires several levels of algorithmic accumulation of basic recognized events", "location": "§INTRODUCTION, p. 2" }, "whoCares": { "summary": "AI and HCI researchers building systems that translate machine recognition into output for people, such as voice assistants and assistive technology for visually impaired meeting participants.", "quote": "we strongly encourage specialists from both fields to start considering the degrees of minimal required interpretability in AI systems", "location": "§CONCLUSION, p. 4" } }, "researchQuestions": [ "How do visually impaired people experience social dynamics in work meetings, and what additional information would they find useful?", "How do people narrate the visual social attention cues of a meeting for a visually impaired person, and what structure do those descriptions have?" ], "concepts": [ { "term": "Interpretation gap", "definition": "The problem the paper names:", "quote": "the gap between the degree of atomization of labels produced by machine recognition and the complexity of system output required for human comprehension", "location": "§INTRODUCTION, p. 2" }, { "term": "Social attention", "definition": "Why machine labels of pose and gaze are not enough:", "quote": "social attention is above all a progressive process of selection of cues that lies as much in human sense-making abilities as it does in their physical abilities", "location": "§INTRODUCTION, p. 2" }, { "term": "Actor, target and attention identifier", "definition": "The elements of the authors' model of attention descriptions: who attends (individual or collective), what they attend to (content, object or human), and the verb naming the act of attention.", "quote": "descriptions identified an actor element as a source of a 'attention action' (the 'who' of an attention description), differentiated as individual and collective", "location": "§Study II: How people narrate the social attention cues of a meeting, p. 3" } ], "method": { "design": "Two preliminary studies: semi-structured interviews, then a quasi-experimental narration study.", "setting": "Work meetings. In Study II, participants narrated muted video recordings of meetings to an imaginary visually impaired person, focusing on social dynamics.", "sample": "Study I: ten visually impaired employees from diverse types of organizations. Study II: 15 participants, each shown six ~2 min videos of work meetings with 4 to 6 meeting participants.", "analysis": "Qualitative analysis of interview accounts and of narrated descriptions, used to build a structural model of social attention description." }, "findings": [ { "headline": "Blind employees want body language.", "summary": "Ten visually impaired employees from diverse organisations wanted to know what other people's body language and attention conveyed in meetings, much of which rests on signals that machine vision could potentially recognise.", "quote": "It would be really helpful to know what people's body language was saying. So you know, bored, or engaged, or distrusted, or stressed.", "location": "§Study I: How visually-impaired people experience social dynamics in meetings, pp. 2–3", "url": "https://seanrintel.com/publications/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines.html#at-sstudy-i-how-visually-impaired-people-experience-social-dynamics-in-meetings-pp-2-3", "cite": "Anastasia Kuzminykh and Sean Rintel. 2019. Meeting in the Middle: The Interpretation Gap Between People and Machines. CHI 2019. (§Study I: How visually-impaired people experience social dynamics in meetings, pp. 2–3)" }, { "headline": "Raw cues, not verdicts.", "summary": "They saw the information they wanted as objective and elemental, and preferred to receive it unprocessed so that they could interpret it themselves.", "quote": "And I think \"someone is taking notes\", \"someone is reading notes\", \"someone is looking at the window\" is fine.", "location": "§Study I: How visually-impaired people experience social dynamics in meetings, pp. 2–3", "url": "https://seanrintel.com/publications/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines.html#at-sstudy-i-how-visually-impaired-people-experience-social-dynamics-in-meetings-pp-2-3-2", "cite": "Anastasia Kuzminykh and Sean Rintel. 2019. Meeting in the Middle: The Interpretation Gap Between People and Machines. CHI 2019. (§Study I: How visually-impaired people experience social dynamics in meetings, pp. 2–3)" }, { "headline": "Structured, but interpretive.", "summary": "When 15 people narrated muted meeting videos for an imagined visually impaired listener, their descriptions were structured enough for the authors to model, but their elements were still accumulative and interpretive.", "quote": "participants' descriptions were granular enough for us to develop a structural model of social attention description (see Fig.2), the elements of descriptions still often had an accumulative and interpretive nature", "location": "§Study II: How people narrate the social attention cues of a meeting, p. 3", "url": "https://seanrintel.com/publications/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines.html#at-sstudy-ii-how-people-narrate-the-social-attention-cues-of-a-meeting-p-3", "cite": "Anastasia Kuzminykh and Sean Rintel. 2019. Meeting in the Middle: The Interpretation Gap Between People and Machines. CHI 2019. (§Study II: How people narrate the social attention cues of a meeting, p. 3)" }, { "headline": "Groups take more work to recognise.", "summary": "Attention to one person might be recognised from a single video frame, but attention to a group, as in this narration, has to be assembled from several individual acts of attention.", "quote": "The lady is sitting and listening to both of them", "location": "§Study II: How people narrate the social attention cues of a meeting, p. 3", "url": "https://seanrintel.com/publications/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines.html#at-sstudy-ii-how-people-narrate-the-social-attention-cues-of-a-meeting-p-3-2", "cite": "Anastasia Kuzminykh and Sean Rintel. 2019. Meeting in the Middle: The Interpretation Gap Between People and Machines. CHI 2019. (§Study II: How people narrate the social attention cues of a meeting, p. 3)" }, { "headline": "Verbs that go beyond what is seen.", "summary": "Narrators named acts of attention with many interpretive verbs, which go well beyond the visual information they were derived from.", "quote": "\"to look\", \"to watch\", \"to listen\", \"to pay attention\", \"to direct attention\", \"to be attentive to\", \"to be engaged\", \"to talk to\", \"to have a conversation with\"", "location": "§Study II: How people narrate the social attention cues of a meeting, p. 3", "url": "https://seanrintel.com/publications/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines.html#at-sstudy-ii-how-people-narrate-the-social-attention-cues-of-a-meeting-p-3-3", "cite": "Anastasia Kuzminykh and Sean Rintel. 2019. Meeting in the Middle: The Interpretation Gap Between People and Machines. CHI 2019. (§Study II: How people narrate the social attention cues of a meeting, p. 3)" } ], "questions": [ { "question": "What do visually impaired people want to know about what's happening in a meeting?", "answer": "Body language and attention, such as whether others are engaged, attentive, confused or supportive. Visually impaired employees interviewed about meetings saw this as objective information. They preferred to receive it unprocessed, so that they could interpret it themselves.", "source": "Anastasia Kuzminykh and Sean Rintel. 2019. Meeting in the Middle: The Interpretation Gap Between People and Machines. CHI 2019.", "basedOn": [ { "location": "§Study I: How visually-impaired people experience social dynamics in meetings, pp. 2–3", "url": "https://seanrintel.com/publications/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines.html#at-sstudy-i-how-visually-impaired-people-experience-social-dynamics-in-meetings-pp-2-3" }, { "location": "§Study I: How visually-impaired people experience social dynamics in meetings, pp. 2–3", "url": "https://seanrintel.com/publications/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines.html#at-sstudy-i-how-visually-impaired-people-experience-social-dynamics-in-meetings-pp-2-3-2" } ] }, { "question": "Can machine vision describe social dynamics in meetings to blind users?", "answer": "Many relevant signals, such as gestures and body pose, are potentially recognisable by machine vision. But the descriptions people expect are interpretive and accumulative, so a system would need to combine basic labels into higher-level events before they are meaningful to a listener.", "source": "Anastasia Kuzminykh and Sean Rintel. 2019. Meeting in the Middle: The Interpretation Gap Between People and Machines. CHI 2019.", "basedOn": [ { "location": "§Study I: How visually-impaired people experience social dynamics in meetings, pp. 2–3", "url": "https://seanrintel.com/publications/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines.html#at-sstudy-i-how-visually-impaired-people-experience-social-dynamics-in-meetings-pp-2-3" }, { "location": "§Study II: How people narrate the social attention cues of a meeting, p. 3", "url": "https://seanrintel.com/publications/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines.html#at-sstudy-ii-how-people-narrate-the-social-attention-cues-of-a-meeting-p-3" }, { "location": "§Study II: How people narrate the social attention cues of a meeting, p. 3", "url": "https://seanrintel.com/publications/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines.html#at-sstudy-ii-how-people-narrate-the-social-attention-cues-of-a-meeting-p-3-2" } ] }, { "question": "Is a description like 'she is listening' objective?", "answer": "Not to a machine. People treat it as plain observation, but it interprets gaze and posture as an act of attention, and attention to a group must be pieced together from several individual acts. Such summaries spare a listener overload, so systems need rules for building them.", "source": "Anastasia Kuzminykh and Sean Rintel. 2019. Meeting in the Middle: The Interpretation Gap Between People and Machines. CHI 2019.", "basedOn": [ { "location": "§Study II: How people narrate the social attention cues of a meeting, p. 3", "url": "https://seanrintel.com/publications/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines.html#at-sstudy-ii-how-people-narrate-the-social-attention-cues-of-a-meeting-p-3" }, { "location": "§Study II: How people narrate the social attention cues of a meeting, p. 3", "url": "https://seanrintel.com/publications/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines.html#at-sstudy-ii-how-people-narrate-the-social-attention-cues-of-a-meeting-p-3-2" }, { "location": "§Study II: How people narrate the social attention cues of a meeting, p. 3", "url": "https://seanrintel.com/publications/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines.html#at-sstudy-ii-how-people-narrate-the-social-attention-cues-of-a-meeting-p-3-3" } ] } ], "cites": [], "quantitative": [], "implications": [ { "summary": "Research should explore how people build accumulative descriptions and turn them into machine recognition rules, since these reduce the listener's cognitive overload.", "quote": "it is important that research continues to explore further the mechanisms of accumulative descriptions and formulate them as machine recognition rules", "location": "§Study II: How people narrate the social attention cues of a meeting, p. 3" }, { "summary": "AI and HCI researchers should work together, with HCI articulating the requirements for applying machine recognition in human-oriented technology, including the minimal interpretability systems need.", "quote": "we strongly encourage specialists from both fields to start considering the degrees of minimal required interpretability in AI systems to advance the possibilities of systems applications", "location": "§CONCLUSION, p. 4" } ], "limitations": [ { "summary": "The results are preliminary, and understanding of the right degree of interpretability is at a very early stage.", "quote": "We are still at the very early stages of understanding how to identify the appropriate degree of interpretability", "location": "§CONCLUSION, p. 4" } ], "figures": [ { "src": "https://seanrintel.com/publications/figures/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines/fig-2.webp", "caption": "Figure 2: Structural model of human-produced descriptions of social attention.", "alt": "Diagram: an actor (collective or individual) directs attention, with a purpose, at a target (content, object, or human, itself collective or individual), and the whole description can be immediate or accumulative.", "location": "Fig. 2, p. 3", "credit": "Figure 2 from Anastasia Kuzminykh and Sean Rintel. 2019. Meeting in the Middle: The Interpretation Gap Between People and Machines. CHI 2019." } ], "pageNumbersReferTo": "https://seanrintel.com/publications/meeting-in-the-middle-the-interpretation-gap-between-people-and-machines.pdf", "verified": "2026-10-25", "studyFigure": { "about": "The opening figure on this paper's page, made for the site with AI assistance from this verified brief. It is not the paper's own figure. Evidence entries index this file's quantitative, findings and limitations arrays.", "study": { "kind": "single", "summary": "Two preliminary qualitative studies. Ten visually impaired employees were interviewed, then 15 people narrated muted meeting videos for an imagined visually impaired listener.", "steps": [ { "label": "Ten employees", "detail": "Visually impaired employees from diverse types of organisations, interviewed about social dynamics in work meetings." }, { "label": "15 narrators", "detail": "Each narrator watched six muted videos of work meetings, about two minutes long, with 4 to 6 people in each." }, { "label": "Narrating for a listener", "detail": "Narrators described the social dynamics of each meeting to an imaginary visually impaired person." }, { "label": "Modelling descriptions", "detail": "The narrations were analysed to build a model of who attends, to what, and the verb naming the act." } ] }, "findings": { "legend": null, "stages": [ { "title": "What visually impaired employees wanted", "sub": "interviews with ten employees", "items": [ { "dir": "none", "text": "Interviewees described wanting to know what colleagues' body language and attention conveyed.", "detail": "Much of this information rests on signals that machine vision could potentially recognise.", "evidence": [ "findings[0]" ] }, { "dir": "none", "text": "Interviewees described wanting raw cues to interpret, not processed verdicts.", "detail": "Interviewees saw cues such as someone taking notes as objective and elemental, and preferred to interpret them themselves.", "evidence": [ "findings[1]" ] } ] }, { "title": "How narrators described attention", "sub": "narrations by 15 people", "items": [ { "dir": "none", "text": "Narrators' descriptions were structured enough to model, yet still interpretive.", "detail": "Many elements of the descriptions were built up from several cues, adding up to more than any single visible signal.", "evidence": [ "findings[2]" ] }, { "dir": "none", "text": "Narrators assembled attention to a group from several individual acts of attention.", "detail": "Attention to one person might be read from a single video frame. Someone listening to both of two speakers needs several such acts added up.", "evidence": [ "findings[3]" ] }, { "dir": "none", "text": "Narrators named acts of attention with many interpretive verbs.", "detail": "Verbs such as to listen, to pay attention and to be engaged go well beyond the visual information they came from.", "evidence": [ "findings[4]" ] } ] }, { "title": "What the paper argues", "sub": "from preliminary results", "items": [ { "dir": "none", "text": "The paper argues machine descriptions of meetings must bridge an interpretation gap.", "detail": "Machine recognition yields many small pose and gaze labels, while people need richer descriptions. The paper notes these results are preliminary.", "evidence": [ "takeaway", "limitations[0]" ] } ] } ] }, "keyTerm": "interpretation gap", "takeaway": "Machine descriptions of meetings may help visually impaired people by combining pose and gaze cues. Social attention is selective sense making, so even simple cues leave an interpretation gap." } }