Aspen Digital

The development of artificial intelligence (AI) will have profound implications for our world. Already, there are many positive use cases that people are exploring, like solving the scientific puzzle of protein folding, improving global climate modeling, and helping spot dangerous landmines left behind from past wars. At the same time, many have raised valid concerns that AI could be used to accelerate mis- and disinformation, disrupt the labor force, or even cause large-scale catastrophes.

As we sort through these implications, mitigating the harms and taking advantage of the benefits, we need to be thoughtful and listen carefully to a diverse set of voices. A wide-ranging, well-informed public conversation is essential. Journalists have an important role to play in educating the public and helping people to understand how AI is showing up in their lives.

The Challenge

But AI is complicated, even for technical experts. For the general public, it can be tough to follow what the technology even does and how it actually works, to separate popular misconceptions and industry hype from reality.

Even for people with the best intentions, it’s easy to fall back on inaccurate or misleading tropes when talking about these emerging technologies. Sometimes, reporters use personification as a tool to help people understand how AI works or what AI is doing. Terms like “learned” or “understood” get thrown around frequently because they relate to how humans make sense of information. Although personification can be useful, it can lead people to believe that AI systems are more capable than they really are.

At the same time that the popular conversation makes these computers seem more human, it can also obscure the roles that actual humans play in creating, shaping, and using artificial intelligence. Real people decide how AI systems are designed and what outcomes they are built to prioritize. Engineers, product managers, IT professionals, and everyday users are the ones who decide how these systems get used in the world. Even the training process, much of which happens algorithmically, involves humans. Despite all the attention on ChatGPT, for example, there has been relatively little focus on the workers behind the tool who continue to fine-tune the model. Talking about the AI model itself as the agent obfuscates all the people involved in the process.

The Solution

The best AI journalism avoids these pitfalls. It communicates clearly about how AI models are trained and developed, what these systems actually do when used, and who is involved with each of these processes and decisions. Great descriptions of AI usually do the following: 

• Use accessible language to convey meaning and define terminology where appropriate
• Emphasize human actors (whether as individuals or organizations, or in professional roles) when describing the creation, deployment, and impacts of AI tools
• Employ action verbs appropriate to non-living systems (e.g. “generates,” “produces,” or “processes,” rather than “writes,” “believes,” or “understands”).
  Note: while generally best avoided, personifying terms may be acceptable when clearly used in simile or within “scare quotes.”
• Describe current capabilities of AI tools in a factual manner, distinct from marketing claims.

Examples of Great A.I. Reporting

Below are some examples of excellent descriptions of AI that we’ve come across:

In our work with journalists, we’ve uncovered a need to elevate more great examples of AI reporting. That’s why we put out an open call for submissions of great short descriptions of AI from 2023. We will compile the examples into the Aspen Digital Reporting on AI Hall of Fame:

transcript

Search Transcript

thanks everyone uh for joining in wehave as I mentioned a specialannouncement and I’m going to turn itover to my fantastic colleague um Tomlowski who’s going to talk us throughwhat we are announcingtoday all right well thank you so much Band thank you to CC and all of ouramazing panelists today for being heresuch a such an exciting event um ifthere’s been one central theme today ofmany it is a lot of uncertainty aboutwhat the future will look like and howAI technology will develop just tohighlight that a little bit StephenHawking said that AI could spell the endof the human race Mark Andre thinks AIcan make everything we care about betterHillary Clinton has said we’re racinghead first and we’re unprepared Yan laonof meta has said we should not see AI asa threat we should see it as beneficialvice president Harris thinks that AI hasthe potential for profound good andprofound harm and President Barack Obamahas said it’s clear by now that AI willaffect us all and I share this to reallyemphasize that people disagree there’snot one unified Narrative of what thefuture is going to be like it peoplehave opinions spanning from the end ofthe human race to everything is fine andeverything we’re going to live in aUtopia to profound impacts on Democracyon the labor force to profound positivesthat could come to Consumers to all ofus and so what does this mean it means acouple things first it means that weneed to be thoughtful and it also meansthat we need to make sure that a lot ofpeople have a voice that everyone canhave a voice in this conversationbecause we don’t know what the futurewill look like and so we need to listencarefully to one another and so this isone of the central drivers of Aspendigitals work and so as we’ve mentioneda couple times um one of the centralthings we’ve done in this vein is ouremerging Tech primers um which you canaccess at this URL and in the chat um westarted the process of creating theseprimers over a year ago they startedwith interviews with journalists whichtransitioned into a series of salonswith experts on AI and eventually wepublished three AI primers reallyinitially intended to help journalistsas they figure out how do we report onAI how do we talk about AI they wereboth designed for Tech journalists andalso for non-tech journalists right forthe folks as we heard CC mention whocover other beats but who arerecognizing well AI is affectingHealthcare or AI is affecting Finance orpolitics and really need to be catchingup on these newtechnologies so I’m going to quickly gothrough those three primers firstthere’s finding experts in AI this hasseveral components one is informationabout common roles in AI one is adirectory of experts so how do you getin touch with the right people who doyou need to talk to to learn more aboutAi and as well as we have notableconferences in AI right so so where arepeople Gathering where are theseconversations ation happening second oursecond primer of three is the intro togenerative AI this highlights what isgenerative AI how does it actually workwhat does it mean and also goes intoseveral key issues so those include thefuture of work intellectual propertyinformation ecosystems the effect ofgenerative AI on our ability to talk toone another and to have a shared senseof Truth and severalothers and finally our third primer AI101 this goes into the very ground levelwhat is AI what are we even talkingabout what does all this mean people saythe algorithm what does that mean whenpeople say AI what does that mean and wealso discuss how to talk better about AIso here is our view of what the bestsentences on AI look like we think theygenerally take the form of people whouse specific AI tools or capabilities todo tasks so just to highlight each pieceof that first people right so we’re notnot just talking about AI as an agentwe’re talking about the people whodesigned the system who trained thesystem who are deploying the system andmaking those decisions about how it getsused second specific tools orcapabilities we think it’s important toget away from talking about AI as onething and it’s far more helpful to talkabout specific tasks specificcapabilities that AI has and finally thetask portion we want to get away frommarketing speak fromyou know projections about what thingscould look like we want to talkspecifically about what AI is doingnow so I’m going to run through anexample of what a good excerpt about AIlooks like this is a bad excerpt aboutAI I wrote this excerpt about AI um andwe’re gonna go through it and improve itso right now it says the AI has learnedto predict crimes how can this improvewell first has learned this ispersonification right we use thissometimes to help explain to to folkswho are new what’s going on but this isnot actually what’s happening within thesystem right so we can get more specificso this is a little bit better the AImatches crime data with informationabout land use to predict crimes that’sa little bit better but we can keepimproving right now we’re still talkingabout the AI as if it’s one thing we canget a little bit more clear there riskterrain modeling matches crime data withinformation about land use to predictcrimes that’s even better but we cankeep improving predict crimes this ismarketing speak right is that actuallywhat’s happening what does the systemliterally doing we can make this excerptbetter and here we go risk terrainmodeling matches crime data withinformation about land use to identifytrends that could be triggering crimesthis is even more clear but we can do alittle better who is doing this we’restill centering the AI the risk terrainmodeling as the agent here so we canimprove this further by talking aboutwho is actually creating this who isdeploying it so here’s the final versionof this sentence developed by ruerUniversity researchers risk terrainmodeling matches crime data withinformation about land use to identifytrends that could be triggering crimesand CC if you’re still on this sentencemight look familiar because this is froman article in the markup we think thisis an an excellent example of how totalk better aboutAI again what we think this sentencedoes well is it talks about people whouse specific AI tools or capabilities todo tasks so just to highlight that herewe have the people behind the tooldeveloped by Rucker Universityresearchers we have the specific toolthat’s being used risk terrain modelingand we have the specific capabilityavoiding marketing speak talking aboutwhat it’s actually doing it’s matchingcrime data with information about landuse to identify trends that could betriggering crimes this is an excellentexample about how to talk about AI wewant to highlight examples like this andso as part of that effort today we’revery excited to launch our reporting onAI Hall of Fame if you have written anexcerpt about AI or you’ve read anexcerpt about AI in an article we areasking you to submit at this URL wewould love to highlight these exampleswe want to point people towards the bestexamples of reporting on AI so just toquickly run through what we’re lookingfor first we’re looking for Clearlanguage we want these examples ofexcerpts to be accessible to as manypeople as possible we don’t want it touse technical jargon second we’relooking to highlight human actors so sowe again think it’s important that theAI is not the agent in these EXs we’relooking for the humans that aredesigning the systems that are trainingthe systems and that are deploying thesystems third we want to describecurrent capabilities so we’re trying toavoid marketing speak in these excerptswe’re trying to describe specificallywhat current systems aredoing and finally and this is Central wewant to avoid personification right sowe think it’s really important to talkabout what the AI is literally doing notusing uh you know figurative languagethere is a time in place for that wordslike learn or understand sometimes canbe helpful when folks are are new but wethink it’s important that these excerptsmake clear what is literally going onwithin the system so again we’re askingall of you if you’ve written somethingif you’ve read something whatever submitto our AI Hall of Fame you can do so atthis link below and hopefully it’s inthe chat as well our deadline forsubmission is the end of January so youhave until January 31st 2024 again thiscan be something you’ve written can besomething you’ve read as long as it’s anexcellent example of AI writing we wantto highlightit thank you very much I will pass itback toB thank thank you so much Tom and thankyou everyone for joining us here todaywe are so excited to be launching theHall of Fame and I’ll just say again weencourage a wide range of submissionshere are you uh involved with a studentjournalism Outlet are you involved witha school newspaper we would love tohighlight great technology journalismthere if you are someone who is umsharing around a sharing about a Englishlanguage um publication from around theworld we would love to include as manydifferent examp examples of greatdescriptions of AI that we can find soum please do this and the reason we’redoing this is because what we heard whenwe did those initial interviews withjournalists back in the DayDay when wefirst started this project what we heardfrom folks is I need good examples tomodel after I need templates I canfollow I need examples that showcasewhat good reporting and goodcommunication looks like and as weexpanded this work out from journaliststo reach broader audiences in governmentin nonprofits and education what wefound is the same is true everyone needsgood examples so by contributing yourgood examples um we can make uh make theconversation about AI a little bitbetter so with that I want to bring usto a close here thank you so much to ourpanelists Victoria Alex Clarence CCE forour fireside chat absolute Joy um it’sbeen so wonderful having you all herewith us thank you all everyone joiningin from home um who participated in ouraudience Q&A really appreciate all ofthe thoughtful questions that you allsubmitted looking forward to the nextone and I hope that you will join uswelcome you to follow us on LinkedIn Ibelieve we have a Twitter account um wehave uh uh our team and our paneliststagged in our LinkedIn posts um andabsolutely please do sign up for ournewsletter so you can stay tuned for allof the upcoming events a big thank youto our funders at seagull familyendowment who’ve been incrediblePartners in this work we couldn’t do itwithout you thanks so much everyone hopeyou have a great rest of yourday