[{"data":1,"prerenderedAt":144},["ShallowReactive",2],{"slug-science-needs-a-better-way-to-think-about-the-future":3},{"post":4,"relatedPosts":142,"relatedBooks":143},{"id":5,"date":6,"date_gmt":7,"guid":8,"modified":10,"modified_gmt":11,"slug":12,"status":13,"type":14,"link":15,"title":16,"content":18,"excerpt":21,"author":23,"featured_media":24,"comment_status":25,"ping_status":25,"sticky":26,"template":27,"format":28,"meta":29,"categories":30,"tags":34,"project_category":35,"contact_email_category":36,"yst_prominent_words":37,"class_list":38,"better_featured_image":48,"acf":79,"yoast_meta":87,"_links":89},61047,"2026-07-31T10:39:33","2026-07-31T08:39:33",{"rendered":9},"https:\u002F\u002Fmedicalfuturist.com\u002F?post_id=61047&_wpnonce=3155b40385&status=auto-draft&type=post","2026-07-31T10:39:34","2026-07-31T08:39:34","science-needs-a-better-way-to-think-about-the-future","publish","post","https:\u002F\u002Fmedicalfuturist.com\u002Fscience-needs-a-better-way-to-think-about-the-future",{"rendered":17},"Science Needs A Better Way To Think About The Future",{"rendered":19,"protected":20},"\n\u003Cp>Our new \u003Ca href=\"https:\u002F\u002Fwww.nature.com\u002Farticles\u002Fd41586-026-02231-y\">Nature Comment\u003C\u002Fa> introduces “\u003Cstrong>translational foresight\u003C\u002Fstrong>”: a framework for bringing futures methods into the everyday machinery of science\u003C\u002Fp>\n\n\n\n\u003Cp>Every research programme is, in one way or another, a bet on the future. When a university builds a new laboratory, when a funding agency commits millions to a research programme, when a medical school redesigns its curriculum, or when researchers decide which technologies deserve years of investigation, they are making assumptions about what the future will look like. They assume certain technologies will mature, that particular skills will become important, that regulators will accept new approaches, that patients and the public will trust them, and that infrastructure built today will still make sense years from now.\u003C\u002Fp>\n\n\n\n\u003Cp>Yet these assumptions are rarely made explicit. This is the problem we address in our new Comment published in Nature, “The science of foresight: how to future-proof your research.” Together with Tamás Kristóf, Josip Car, Joseph Sung and Tien Yin Wong, we argue that science needs a systematic way to examine the futures it is already implicitly betting on. We call this approach translational foresight.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Not predicting the future, but preparing for it\u003C\u002Fh2>\n\n\n\n\u003Cp>The problem is not that scientists cannot predict the future. They should not be expected to. The future is inherently uncertain, particularly in rapidly evolving fields such as artificial intelligence, genomics, biotechnology and digital health. The problem is that scientific institutions often make long-term decisions while treating the assumptions behind those decisions as if they were fixed.\u003C\u002Fp>\n\n\n\n\u003Cp>The COVID-19 pandemic offered an extreme example. Research organisations and healthcare systems suddenly had to accelerate vaccine development, expand telemedicine, move education online, redeploy healthcare professionals and deal with questions of public trust, surveillance and vaccination. Many of these challenges could not have been predicted in detail, but the possibility of a global health crisis, workforce disruption, rapidly scaling remote healthcare and widespread public distrust could certainly have been explored beforehand.\u003C\u002Fp>\n\n\n\n\u003Cp>Artificial intelligence presents a similar challenge today. Universities, healthcare institutions and research organisations already need to make decisions about AI validation, research integrity, workforce preparation, regulation and governance. They must do so before decades of evidence become available. Waiting for certainty is therefore not an option. The alternative is not prediction. It is foresight.\u003C\u002Fp>\n\n\n\n\u003Cp>Futures studies already has mature methods for systematically examining possible change. These include horizon scanning, scenario analysis, forecasting, backcasting and tools for exploring the second- and third-order consequences of emerging trends. Such approaches are widely used in policy, government and parts of industry, but they remain surprisingly peripheral to everyday scientific practice. \u003C\u002Fp>\n\n\n\n\u003Cp>\u003Cstrong>Our proposal is to bring these methods inside the scientific process itself.\u003C\u002Fstrong> Foresight should not sit somewhere outside science, producing reports about what the future might look like. It should help researchers decide what to investigate, fund, build, teach, validate and evaluate. That is what we mean by translational foresight.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Translational medicine has done it before\u003C\u002Fh2>\n\n\n\n\u003Cp>There is an important historical parallel here. By the late twentieth century, biomedical science had become extraordinarily good at generating discoveries, but there was a growing recognition that scientific discoveries did not automatically translate into better patient outcomes. A gap existed between the laboratory and the clinic. That led to the rise of translational medicine and concepts such as “bench to bedside.” The scientific ecosystem gradually adapted. New funding programmes appeared, institutions dedicated to translational research were created, training programmes changed, and researchers increasingly considered how discoveries could move towards practical impact.\u003C\u002Fp>\n\n\n\n\u003Cp>We believe a similar gap exists today. Futures research already provides sophisticated ways to analyse uncertainty, emerging trends and alternative futures, but those outputs rarely translate into the mechanisms governing science itself. Hence the term translational foresight. The goal is to translate plausible futures into better scientific decisions.\u003C\u002Fp>\n\n\n\n\u003Cp>One concern about futures thinking is that it can sound abstract. It does not have to be. Imagine a research group preparing a five-year grant application. Normally, the team proposes a research plan based on what its members currently know. With a foresight layer added, they might also ask what would happen if a competing technology developed much faster than expected, if regulation changed, if access to an essential dataset became restricted, if the platform on which the research depended became obsolete, or if public acceptance developed differently than expected.\u003C\u002Fp>\n\n\n\n\u003Cp>The team does not need to create a perfect prediction. Instead, it identifies which assumptions the project depends on and which signals would indicate that those assumptions are beginning to fail. The research plan becomes more adaptive as a result. That is a fundamentally different way of thinking about scientific robustness.\u003C\u002Fp>\n\n\n\n\u003Cp>In our Nature Comment, we deliberately included practical methods that researchers could apply without becoming professional futurists. One is the Futures Wheel, which maps the direct and indirect consequences of a development. Take the statement that AI can now co-author scientific papers. What happens next, and what happens because of those consequences? Mapping those ripple effects can reveal opportunities, risks and unintended consequences that are easy to miss when examining only the technology itself.\u003C\u002Fp>\n\n\n\n\u003Cp>Another tool is scenario analysis. Instead of asking what will happen, researchers construct several plausible future environments and test whether their strategy works across them. Backcasting reverses the direction of thinking: researchers imagine a desired future outcome, perhaps the state of their discipline in 2035, and work backwards to identify what would need to happen to get there. We also describe a method we call Stump the Futurist, in which researchers actively try to break a future claim by identifying failure modes, missing variables and hidden assumptions. The point of all these exercises is not to make science speculative. It is almost the opposite. They force assumptions about the future to become explicit enough to be challenged.\u003C\u002Fp>\n\n\n\n\u003Ch2 class=\"wp-block-heading\">Three steps towards translational foresight\u003C\u002Fh2>\n\n\n\n\u003Cp>We propose three broad changes to scientific practice. First, futures methods should become part of ordinary scientific workflows. Researchers could stress-test projects before submitting grants, examine the possible consequences of new technologies and revisit assumptions as new evidence appears. \u003C\u002Fp>\n\n\n\n\u003Cp>Second, futures literacy should become part of scientific education. Researchers learn statistics because they need to interpret uncertainty in data, and they learn methodology because they need to design rigorous experiments. We argue that they should also learn how to reason systematically about uncertainty in the future. Futures literacy could eventually become a basic scientific competency.\u003C\u002Fp>\n\n\n\n\u003Cp>Third, foresight should become institutionalised. Funding agencies, universities and research organisations could incorporate long-term assumptions and alternative futures into funding decisions, infrastructure planning and project evaluation. This is where the idea becomes much bigger than a workshop exercise. If funding systems begin asking researchers not only, “What do you expect to discover?” but also, “Under what future conditions would your assumptions stop being valid?”, the incentives of science itself start to change.\u003C\u002Fp>\n\n\n\n\u003Cp>This matters especially now because science has always had to deal with uncertainty, but the speed at which technological and societal conditions can transform is increasing. Artificial intelligence can reshape an entire research workflow within a few years. New biological tools can emerge faster than the regulatory structures surrounding them. Healthcare technologies can move from experimental to consumer products before institutions have decided how they should be evaluated. At the same time, scientific programmes themselves can take five, ten or twenty years to mature.\u003C\u002Fp>\n\n\n\n\u003Cp>I have spent much of my career trying to \u003Ca href=\"https:\u002F\u002Fwww.jmir.org\u002F2024\u002F1\u002Fe57148\">make futures methods accessible\u003C\u002Fa> to medicine and healthcare. One recurring obstacle has been the misconception that thinking about the future means trying to predict it. It does not. The real goal is to improve decisions made today. A good foresight process does not tell researchers what the world will look like in 2035. It helps them understand which assumptions they are making about 2035, which of those assumptions matter most, how those assumptions might fail, and what they could do differently as a result.\u003C\u002Fp>\n\n\n\n\u003Cp>That is a much more useful ambition, and one that science can realistically adopt. Our Nature Comment ends with a sentence that captures the idea:\u003C\u002Fp>\n\n\n\n\u003Cblockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n\u003Cp>“The twentieth century taught science how to translate discovery into impact. The twenty-first century must teach it how to translate plausible futures into better scientific decisions.”\u003C\u002Fp>\n\u003C\u002Fblockquote>\n\n\n\n\u003Cp>That is what translational foresight is ultimately about: not predicting science, but future-proofing the way we do it.\u003C\u002Fp>\n\n\n\n\u003Cp>\u003Ca href=\"https:\u002F\u002Fmedia.nature.com\u002Fw1248\u002Fmagazine-assets\u002Fd41586-026-02231-y\u002Fd41586-026-02231-y_52981536.jpg?as=webp\">The Nature Comment: The science of foresight: how to future-proof your research, by Bertalan Meskó, Tamás Kristóf, Josip Car, Joseph Sung and Tien Yin Wong, published in Nature, Volume 655, 23 July 2026.\u003C\u002Fa>\u003C\u002Fp>\n",false,{"rendered":22,"protected":20},"\u003Cp>Our new Nature Comment introduces “translational foresight”: a framework for bringing futures methods into the everyday machinery of science Every research programme is, in one […]\u003C\u002Fp>\n",6,61051,"closed",true,"","standard",{"_acf_changed":20,"footnotes":27},[31,32,33],7079,6261,798,[],[],[],[],[39,14,40,41,42,43,44,45,46,47],"post-61047","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tmf","category-forecast","category-digital-health-research",{"id":24,"alt_text":27,"caption":27,"description":27,"media_type":49,"media_details":50,"post":5,"source_url":78},"image",{"width":51,"height":52,"file":53,"filesize":54,"sizes":55,"image_meta":75},1500,643,"2026\u002F07\u002FChatGPT-Image-Jul-31-2026-10_36_36-AM.png",1395925,{"medium":56,"large":63,"thumbnail":69,"medium_large":74},{"file":57,"width":58,"height":59,"mime-type":60,"filesize":61,"source_url":62},"ChatGPT-Image-Jul-31-2026-10_36_36-AM-370x208.png",370,208,"image\u002Fpng",109631,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F07\u002FChatGPT-Image-Jul-31-2026-10_36_36-AM-370x208.png",{"file":64,"width":65,"height":66,"mime-type":60,"filesize":67,"source_url":68},"ChatGPT-Image-Jul-31-2026-10_36_36-AM-768x329.png",768,329,339842,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F07\u002FChatGPT-Image-Jul-31-2026-10_36_36-AM-768x329.png",{"file":70,"width":71,"height":71,"mime-type":60,"filesize":72,"source_url":73},"ChatGPT-Image-Jul-31-2026-10_36_36-AM-150x150.png",150,33799,"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F07\u002FChatGPT-Image-Jul-31-2026-10_36_36-AM-150x150.png",{"file":64,"width":65,"height":66,"mime-type":60,"filesize":67,"source_url":68},{"aperture":76,"credit":27,"camera":27,"caption":27,"created_timestamp":76,"copyright":27,"focal_length":76,"iso":76,"shutter_speed":76,"title":27,"orientation":76,"keywords":77},"0",[],"https:\u002F\u002Fcdn.medicalfuturist.com\u002Fwp-content\u002Fuploads\u002F2026\u002F07\u002FChatGPT-Image-Jul-31-2026-10_36_36-AM.png",{"cta_type":27,"cta_color":27,"subtitle":27,"key_takeaways":80,"related_books":20,"related_posts_footer":20,"related_posts":20},[81,83,85],{"title":82},"\u003Cp>Our new Nature Comment introduces “translational foresight”: a framework for bringing futures methods into the everyday machinery of science\u003C\u002Fp>\n",{"title":84},"\u003Cp>The world in which a research programme begins may be very different from the one in which its results finally arrive. That makes the ability to systematically explore possible futures increasingly important.\u003C\u002Fp>\n",{"title":86},"\u003Cp>This article summarizes the paper.\u003C\u002Fp>\n",{"yoast_wpseo_title":88,"yoast_wpseo_metadesc":27,"yoast_wpseo_canonical":15},"Science Needs A Better Way To Think About The Future - The Medical Futurist",{"self":90,"collection":96,"about":99,"author":102,"replies":105,"version-history":108,"predecessor-version":112,"wp:featuredmedia":116,"wp:attachment":119,"wp:term":122,"curies":138},[91],{"href":92,"targetHints":93},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F61047",{"allow":94},[95],"GET",[97],{"href":98},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts",[100],{"href":101},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftypes\u002Fpost",[103],{"embeddable":26,"href":104},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fusers\u002F6",[106],{"embeddable":26,"href":107},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcomments?post=61047",[109],{"count":110,"href":111},1,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F61047\u002Frevisions",[113],{"id":114,"href":115},61053,"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fposts\u002F61047\u002Frevisions\u002F61053",[117],{"embeddable":26,"href":118},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia\u002F61051",[120],{"href":121},"https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fmedia?parent=61047",[123,126,129,132,135],{"taxonomy":124,"embeddable":26,"href":125},"category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcategories?post=61047",{"taxonomy":127,"embeddable":26,"href":128},"post_tag","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Ftags?post=61047",{"taxonomy":130,"embeddable":26,"href":131},"project_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fproject_category?post=61047",{"taxonomy":133,"embeddable":26,"href":134},"contact_email_category","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fcontact_email_category?post=61047",{"taxonomy":136,"embeddable":26,"href":137},"yst_prominent_words","https:\u002F\u002Fapi.medicalfuturist.com\u002Fwp-json\u002Fwp\u002Fv2\u002Fyst_prominent_words?post=61047",[139],{"name":140,"href":141,"templated":26},"wp","https:\u002F\u002Fapi.w.org\u002F{rel}",[],[],1785489398376]