AI is swiftly growing in use throughout pretty much every industry. Sometimes the tools are specialized, like SEO-focused analysis tools that offer suggestions on how to maximize your Google search ranking. Other times, they're more generalized, like ChatGPT, used more as toys than as serious tools. Either way, there are a lot of questions you may have about the validity of the information they give you.
Can AI be used for fact-checking? Some people think so, while others think not. Let's look at the issue from a few different angles and see what you need to do as a business or as a freelance writer looking to use AI as part of your toolset.
No. At least, not the common tools currently in use, like Jasper or ChatGPT.
Current AI content generators were trained on large pools of writing, and as a consequence, they can generate very good-sounding content. However, they have a tenuous grasp of fact at best. There are a huge array of examples of asking the AI the reason why some fact or another is true, and it giving nonsensical answers.
It's one thing to know a fact ahead of time, ask the AI about the fact, and get a verifiably incorrect answer. It's another to ask it to generate content out of whole cloth and hope it generates something accurate. You generally need a fact-checker and an AI editor or AI editing service to go over the content an AI writer generates to make sure it's not making claims you don't want to support.
Here's what ChatGPT says right on their homepage:
"ChatGPT sometimes writes plausible-sounding but incorrect or nonsensical answers. Fixing this issue is challenging, as: (1) during RL training, there's currently no source of truth; (2) training the model to be more cautious causes it to decline questions that it can answer correctly; and (3) supervised training misleads the model because the ideal answer depends on what the model knows, rather than what the human demonstrator knows."
AI doesn't have fact-checking built into it. It can say factually true things, of course. It can also say things that aren't true but assume they are.
The key thing to remember is that there's no intelligence behind AI, despite the name. It's all math. All language-model AIs do is perform a vast set of calculations to predict the most likely words that will follow previous words, with X amount of word look-back to make it more coherent as a whole. The AI doesn't think anything or know anything; it just puts words together in an order based on what previous real people have written and have been fed into the machine.
Probably, eventually, maybe.
There are currently a variety of companies pushing to make fact-checking AI systems for use in trust analysis, journalism, verifiability, and other areas. Here's an example of one.
While models like ChatGPT are designed and trained with natural language as the goal and reinforcement towards things that sound good with no inherent reliance on fact, other AI models can be trained with other forms of reinforcement. If one were to create an AI system that was reinforced with factual accuracy as a goal, it could potentially be used for fact-checking.
There are a few significant limitations to this, however.
First of all, it relies on the training data and reinforcement to be correct. If you trained the AI to believe that the sky is pink polka-dotted, it would "know" that as fact and fact-check anything saying the sky is blue as wrong. The AI doesn't have eyes and can't observe the world, identify facts about the world, or use that information on its own. It can only "know" what it is told is correct.
Secondly, the AI can only know things that the people training it know. If no one on the development team is a medical expert, the AI is unlikely to be able to verify medical facts at all. Sure, it could be trained on PubMed, but there's a lot of junk on PubMed, and knowing how to filter the good papers from the bad is a key skill an AI won't have.
Third, there's a lot about the world that people may believe is true, when it isn't. Do you "know" that a bull will get angry and charge a red flag, or that people only use 10% of their brains, or that touching a lost baby bird means the mother will reject it? Common misconceptions can be programmed into an AI because people don't know what they don't know.
Finally, there's a lot about reality that isn't objective. A very simple example is the illustration of point of view; with a symbol painted on the ground, someone standing on one side of it will see a 6, while someone on the other side sees a 9. Neither one is necessarily right or wrong, and an AI can't tell you which is true.
These are the kinds of hurdles that any fact-checking AI will have to overcome if it wants to be trusted itself.
None of the problems above have actually stopped anyone from making AI-based fact-checking systems. So, how do those systems work, and how do they solve those problems?
Essentially, there are three kinds of AI fact-checking systems.
The first strives to be trained on issues and can perform research throughout its database of training material to identify inconsistencies and suggest that something may or may not be correct. Claims that are verifiably incorrect can be spotted, claims that are questionable may be flagged, and claims that are verifiably correct can be given a pass. Anything that falls outside the paradigm, either as a claim that can't be identified as a claim or as a claim that is outside of the AI's area of expertise, will be flagged as unavailable for checking.
There are already a bunch of systems like this in development and in use in small scales, but nothing large enough to be a counterpart to something like GPT.
The second is more of an analysis of the world surrounding the claim. The AI doesn't attempt to make the judgment over whether or not the claim is true; rather, it tries to analyze the source of the claim and identify whether or not it's likely to be trustworthy. This is kind of like what Google already does with their E-A-T analysis, but more AI-driven.
The third is just to be wrong all the time. Plenty of startups are trying to layer various levels of fluff on top of a core system like GPT and claim it can do fact-checking, looking to sell a bunch of licenses before they fold under the pressure of being frauds.
This is all for written content, by the way. There are different AI systems entirely that are trained on recognizing other AI-generated content and AI systems created to identify when an image or video has been edited or manipulated. These have their own benefits and their own challenges, but while they're adjacent to fact-checking, they aren't quite the same, so I've mostly left them out of the discussion.
Very likely, yes.
AI-generated content is going to be very prevalent in the coming years, and that presents two major issues.
The first is the above-mentioned lack of factual verification in common AI systems like GPT. While it's possible that these systems will be trained to be more factual once they've gotten the realistic presentation down, we aren't there yet.
The second and more insidious problem is groups deliberately pushing misinformation. We're seeing this already, from election falsehoods to pandemic misinformation to whatever other agenda anyone with access to a content-generating AI wants to push. An AI can be trained to say whatever its handlers want it to say, and that can include completely incorrect information pushed for an agenda.
There is very likely going to be a crisis of trust regarding content in the near future, more so than there already is with the way viral misinformation can spread on platforms like Facebook and Twitter. It's a problem that will need to be addressed, and there's a significant risk that the people in charge of addressing it aren't moving fast enough.
Of course, it's much easier to lie than it is to call out a lie, so this is a difficult arms race to be involved in. I don't envy the AI designers on the front lines.
Not anytime soon.
The truth of the matter is that AI needs validation and verification to be trained properly, and only humans can do that. AI isn't self-learning or self-sustaining. It is, again, all math at its core.
Training an AI to even recognize the claims being made is an extremely difficult task. Training it to identify the claims being made, validate whether or not they're true, and present sources to prove it is another thing entirely.
We aren't there yet. We probably won't be there for years, though a lot of companies are going to make bold claims in the near future.
There will be a lot of content created by AI and published everywhere on the web in the very near future. There already is a lot more of it than many of us probably want to admit. Understanding its limitations will be a big part of using it effectively if that's what you want to do with the tool.
If you're worried about fact-checking, the best thing you can do is hire subject matter experts you can trust.
There's a reason that sites like WebMD hire doctors to fact-check, why Twitter has embedded fact-checking from verifiable sources, and why sites like Snopes or Politifact exist.
People are better at recognizing the claims being made, identifying the holes in those claims, and either presenting reasons why they aren't valid, sources to prove they are, or just fixing them before publication.
If you're a business producing content, whether you're hiring freelancers to write or using an AI to generate that content, a fact-checker should be part of your editorial process. For the moment, only a real human, and one who is an expert in the subject in the first place, can appropriately handle fact-checking.
More than that, you need fact-checking that holds weight. Either you're staking your business reputation on the facts you present, or you have a third-party individual who is staking their reputation on it. Of course, then you need to validate that those people know what they're talking about and that their reputation is worth anything to them in the first place, or even that they're real. Still, it's a starting point for human fact-checking.
If you're a content creator and you need fact-checking, hiring an editor to handle it is generally your best bet. Even if you use an AI tool to validate the facts in your piece, you still need someone to go over the AI results and validate those because AI can't necessarily be trusted yet.
It's a very complicated problem. I recommend avoiding it entirely until the AI ecosystem gets a lot better than it is now and a few different major problems are shaken out and fixed, if they even can be addressed with current AI models.
Until then, why not check out my job board? I have a ton of resources available for hiring writers of all different kinds, as well as tips for writers to find clients willing to pay them what they're worth. On top of that, I'm working to make my job board the best place for writers, with clients and writers both frequenting the lists. I can't do it without you, though, so check it out!
Additionally, if you ever have any comments, questions, or concerns, you're always more than free to leave those in the comments section down below. I'd love to hear what you think, and would be more than happy to answer any of your potential questions.
It's important to share the news to spread the truth. Most people won't.
AI inazidi kuwa maarufu katika kila sekta. Vifaa vya SEO ni zana za SEO zinazohusika na SEO ambazo hutoa mapendekezo ya jinsi ya kuongeza nafasi yako ya utafutaji wa Google. Wakati mwingine, wao ni zaidi generalized, kama ChatGPT, kutumika zaidi kama toys kuliko kama zana kubwa. Kwa vyovyote vile, kuna maswali mengi ambayo unaweza kuwa nayo kuhusu uhalali wa habari wanayokupa. Je, AI inaweza kutumika kwa ajili ya ukweli-checking? Watu fulani hufikiri hivyo, huku wengine wakifikiri kwamba sivyo. Hebu tuangalie suala hili kutoka pembe kadhaa tofauti na tuone nini unahitaji kufanya kama biashara au kama mwandishi wa kujitegemea kuangalia kutumia AI kama sehemu ya seti yako ya zana. La, sivyo. Kwa hivyo, kwa sasa, hakuna chombo cha kawaida cha kuwasiliana na wavuti kama vile Jasper au ChatGPT. Jenereta za sasa za yaliyomo ya AI zimezoezwa kwenye mabwawa makubwa ya maandishi, na kama matokeo, zinaweza kutengeneza yaliyomo mazuri sana. Hata hivyo, wana ufahamu mdogo wa mambo ya hakika. Kuna aina nyingi za maswali ambayo AI inaweza kutoa kwa sababu ya ukweli fulani au mwingine, na kutoa majibu yasiyo na maana. Ni jambo moja kujua ukweli kabla ya wakati, kuuliza AI kuhusu ukweli, na kupata jibu verifiably makosa. Ni mwingine kuuliza ni kuzalisha maudhui nje ya kitambaa nzima na matumaini ni kuzalisha kitu sahihi. Kwa kawaida unahitaji mtihani wa ukweli na mhariri wa AI au huduma ya uhariri wa AI kwenda juu ya yaliyomo ambayo mwandishi wa AI hutengeneza ili kuhakikisha haitoi madai ambayo hutaki kuunga mkono. "Kama ilivyoelezwa kwenye ukurasa wa kwanza wa wavuti, ""ChatGPT wakati mwingine huandika majibu yanayoonekana kuwa ya kweli lakini sio sahihi au yasiyo na maana.""" "Kufanya hivyo ni changamoto, kama vile: (1) wakati wa mafunzo ya RL, kwa sasa hakuna chanzo cha ukweli; (2) mafunzo ya mfano kuwa makini zaidi husababisha kukataa maswali ambayo inaweza kujibu kwa usahihi; na (3) mafunzo ya kusimamia huongoza mfano kwa sababu jibu bora inategemea kile mfano anajua, badala ya kile mtu anayeonyesha anajua. """ AI haina fact-checking kujengwa ndani yake. Bila shaka, inaweza kusema mambo ya kweli. Pia inaweza kusema mambo ambayo si ya kweli lakini kudhani ni kweli. Jambo muhimu kukumbuka ni kwamba hakuna akili nyuma ya AI, licha ya jina. Yote ni hesabu. Kwa mfano, AI ya lugha ya lugha hufanya seti kubwa ya hesabu ili kutabiri maneno yanayowezekana zaidi ambayo yatafuata maneno ya awali, na X ya idadi ya maneno ya kuangalia nyuma ili kuifanya iwe na mshikamano zaidi. AI haifikirii chochote au haijui chochote; inaweka tu maneno pamoja kwa utaratibu kulingana na kile watu halisi walichoandika na kuingizwa kwenye mashine. Yaelekea, hatimaye, labda. Hivi sasa kuna kampuni mbalimbali zinazoendeleza kufanya mifumo ya AI ya kuangalia ukweli kwa ajili ya matumizi katika uchambuzi wa uaminifu, uandishi wa habari, uthibitishaji, na maeneo mengine. Hapa ni mfano wa moja. Wakati mifano kama vile ChatGPT ni iliyoundwa na mafunzo na lugha ya asili kama lengo na kuimarisha kuelekea mambo ambayo sauti nzuri bila kutegemea asili juu ya ukweli, mifano mingine AI inaweza kufundishwa na aina nyingine ya kuimarisha. Ikiwa mtu angeunda mfumo wa AI ambao uliongezwa na usahihi wa ukweli kama lengo, inaweza kutumika kwa ukaguzi wa ukweli. Hata hivyo, kuna mapungufu machache muhimu katika jambo hilo. Kwanza kabisa, inategemea data ya mafunzo na kuimarisha kuwa sahihi. "Ikiwa utafundisha AI kuamini kwamba anga ni rangi ya waridi polka-dotted, itakuwa ""kujua"" kwamba kama ukweli na ukweli-check chochote kusema anga ni bluu kama makosa." AI haina macho na haiwezi kuchunguza ulimwengu, kutambua ukweli kuhusu ulimwengu, au kutumia habari hiyo peke yake. Inaweza tu "kujua" kwamba kile kinachosemwa ni sahihi. Kwa upande mwingine, AI inaweza tu kujua mambo ambayo watu wanaofundisha wanajua. Ikiwa hakuna mtu katika timu ya maendeleo ni mtaalam wa matibabu, AI haiwezekani kuwa na uwezo wa kuthibitisha ukweli wa matibabu. "Hata hivyo, kuna uwezekano wa kuwa na ""pubmed"" ambayo inaweza kuonekana kama kitu cha kawaida, lakini kwa sababu ya kuonekana kwa ""pubmed"" na ""pubmed,"" ni muhimu sana kuamua ni aina gani ya AI inayotumika." Tatu, kuna mengi kuhusu ulimwengu ambayo watu wanaweza kuamini ni kweli, wakati si hivyo. Je, unajua kwamba ng'ombe-dume ata hasira na kushambulia bendera nyekundu, au kwamba watu hutumia 10% tu ya ubongo wao, au kwamba kugusa ndege mdogo aliyepotea inamaanisha mama atakataa? Mawazo mabaya ya kawaida yanaweza kupangwa katika AI kwa sababu watu hawajui kile hawajui. Mwishowe, kuna mengi kuhusu ukweli ambayo si ya kimakusudi. Mfano rahisi ni mfano wa mtazamo: na alama iliyochorwa ardhini, mtu amesimama upande mmoja ataona sita, wakati mtu mwingine ataona tisa. Hakuna moja ambayo ni sahihi au mbaya, na AI haiwezi kukuambia ni ipi ni kweli. Hizi ni aina ya vikwazo kwamba yoyote ukweli-kuangalia AI itabidi kushinda kama anataka kuaminiwa yenyewe. Hakuna hata moja ya matatizo ya juu ambayo yamemzuia mtu yeyote kutengeneza mfumo wa kuangalia ukweli unaotegemea AI. Kwa hiyo, mifumo hiyo inafanyaje kazi, na jinsi gani hutatua matatizo hayo? Kwa ujumla, kuna aina tatu za AI za kuangalia ukweli. Mwalimu wa kwanza anajitahidi kuwa na mafunzo juu ya masuala na anaweza kufanya utafiti katika hifadhidata yake ya vifaa vya mafunzo ili kutambua kutofautiana na kupendekeza kwamba kitu kinaweza au hakiwezi kuwa sahihi. Madai ambayo ni verifiably makosa inaweza kuonekana, madai ambayo ni ya kutiliwa shaka inaweza kuwa flagged, na madai ambayo ni verifiably sahihi inaweza kupewa kupita. "Kila kitu kinachoanguka nje ya mfano, ama kama madai ambayo hayawezi kutambuliwa kama madai au kama madai ambayo ni nje ya eneo la utaalam wa AI, itaonyeshwa kama haipatikani kwa ajili ya kuangalia. """ Kuna tayari mfumo kama huu katika maendeleo na katika matumizi katika viwango vidogo, lakini hakuna kubwa ya kutosha kuwa mwenzake wa kitu kama GPT. Ya pili ni zaidi ya uchambuzi wa ulimwengu unaozunguka madai. AI haijaribu kufanya uamuzi juu ya ikiwa madai ni kweli au la; badala yake, inajaribu kuchambua chanzo cha madai na kutambua ikiwa ni uwezekano wa kuaminika au la. Hii ni aina ya kile Google tayari hufanya na uchambuzi wao wa E-A-T, lakini zaidi inayoendeshwa na AI. Tatu ni kuwa na makosa wakati wote. "Mashirika mengi ya kuanza yanajaribu kuweka ngazi mbalimbali za ""fluff"" juu ya mfumo wa msingi kama GPT na kudai inaweza kufanya uchunguzi wa ukweli, kuangalia kuuza kundi la leseni kabla ya fold chini ya shinikizo la kuwa udanganyifu." Yote haya ni kwa ajili ya maudhui yaliyoandikwa, kwa njia. Kuna mifumo tofauti ya AI ambayo imezoezwa kutambua yaliyomo mengine yaliyotokana na AI na mifumo ya AI iliyoundwa kutambua wakati picha au video imebadilishwa au kudhibitiwa. Hizi zina faida zao na changamoto zao, lakini wakati wao ni karibu na ukweli-kuangalia, wao si sawa kabisa, hivyo mimi zaidi ya kushoto yao nje ya majadiliano. Yaelekea sana, ndiyo. Kwa hivyo, yaliyomo yaliyotokana na AI yatakuwa ya kawaida katika miaka ijayo, na hiyo inatoa maswala mawili makubwa. "Kwanza, kuna ""kutoweza kuthibitisha ukweli"" katika mifumo ya kawaida ya AI kama GPT." Ingawa ni uwezekano kwamba mifumo hii itakuwa mafunzo kuwa zaidi ya kweli mara moja wao gotten uwasilishaji halisi chini, sisi si huko bado. Tatizo la pili na lenye hila zaidi ni vikundi vinavyosambaza habari zisizo sahihi kimakusudi. "Tunaona hii tayari, kutoka kwa uongo wa uchaguzi hadi habari bandia ya janga, kwa ajali nyingine yoyote ambayo mtu yeyote aliye na upatikanaji wa AI ya kuzalisha yaliyomo anataka kushinikiza. """ AI inaweza kufundishwa kusema chochote wasimamizi wake wanataka waseme, na hiyo inaweza kujumuisha habari isiyo sahihi kabisa iliyoendelezwa kwa ajenda. "Hata hivyo, kuna uwezekano mkubwa wa kuwa na mgogoro wa uaminifu kuhusu maudhui katika siku zijazo, zaidi kuliko ilivyo tayari na njia ya habari mbaya ya virusi inaweza kuenea kwenye majukwaa kama Facebook na Twitter. """ Ni tatizo ambalo linahitaji kushughulikiwa na kuna hatari kubwa kwamba watu wanaohusika na kushughulikia tatizo hilo hawaendi haraka vya kutosha. Ni rahisi kusema uongo kuliko kusema uongo, kwa hiyo ni vigumu kushiriki katika mbio za silaha. Mimi si wivu AI wabunifu juu ya mistari ya mbele. Si wakati wowote hivi karibuni. Ukweli wa jambo ni kwamba AI inahitaji uthibitisho na uthibitisho ili kufundishwa vizuri, na wanadamu tu wanaweza kufanya hivyo. AI haijifundishi yenyewe au kujitegemeza. Ni, tena, yote ya hisabati katika kiini chake. Kufundisha AI kutambua madai ni kazi ngumu sana. Kujifunza jinsi ya kutambua madai yanayotolewa, kuthibitisha kama ni ya kweli au la, na kutoa vyanzo vya kuthibitisha ni jambo jingine kabisa. Hatujafika hapo bado. "Hata hivyo, kwa miaka mingi, ""mashabiki"" wengi wa kampuni hiyo watakuwa na wasiwasi juu ya madai ya haraka katika siku zijazo." Kuna mengi ya yaliyomo iliyoundwa na AI na kuchapishwa kila mahali kwenye mtandao katika siku zijazo. Tayari kuna mengi zaidi ya hayo kuliko wengi wetu wanavyotaka kukiri. Kuelewa mapungufu yake itakuwa sehemu kubwa ya kuitumia kwa ufanisi ikiwa hiyo ni nini unataka kufanya na chombo. Ikiwa una wasiwasi juu ya kuangalia ukweli, jambo bora unaweza kufanya ni kuajiri wataalamu wa mada unaweza kuamini. Kuna sababu kwamba tovuti kama WebMD kuajiri madaktari kwa ukweli-check, kwa nini Twitter ina embedded ukweli-check kutoka vyanzo kuthibitishwa, na kwa nini maeneo kama Snopes au Politifact zipo. Watu ni bora katika kutambua madai yanayotolewa, kutambua mashimo katika madai hayo, na ama kuwasilisha sababu kwa nini si halali, vyanzo vya kuthibitisha wao ni, au tu kurekebisha yao kabla ya kuchapishwa. Ikiwa wewe ni biashara inayotengeneza yaliyomo, iwe unaajiri wafanyikazi wa kujitegemea kuandika au kutumia AI kuunda yaliyomo, mtihani wa ukweli unapaswa kuwa sehemu ya mchakato wako wa uhariri. Kwa sasa, ni mwanadamu halisi tu, na mtu ambaye ni mtaalamu katika somo hilo, anaweza kushughulikia usahihi wa kuangalia ukweli. Zaidi ya hayo, unahitaji kuchunguza mambo yaliyo kweli ambayo yana uzito. Au wewe ni kuhatarisha sifa yako ya biashara juu ya ukweli wewe kuwasilisha, au una mtu wa tatu ambaye ni kuhatarisha sifa yao juu yake. "Bila shaka, basi unahitaji kuthibitisha kwamba watu hao wanajua wanachozungumzia na kwamba sifa yao ina thamani yoyote kwao, au hata kwamba wao ni halisi. """ Hata hivyo, ni hatua ya kuanzia kwa ajili ya uchunguzi wa ukweli wa kibinadamu. Ikiwa wewe ni muundaji wa maudhui na unahitaji kuangalia ukweli, kuajiri mhariri kushughulikia ni kawaida bet yako bora. Hata kama unatumia chombo cha AI kuthibitisha ukweli katika kipande chako, bado unahitaji mtu kwenda juu ya matokeo ya AI na kuthibitisha wale kwa sababu AI haiwezi kuwa na uhakika bado. Ni tatizo gumu sana. "Ninapendekeza kuiepuka kabisa hadi mfumo wa ikolojia wa AI unapopata bora zaidi kuliko ilivyo sasa na matatizo kadhaa makubwa yanashikwa na kurekebishwa, ikiwa yanaweza kushughulikiwa na mifano ya sasa ya AI. """ Hadi wakati huo, kwa nini usichunguze ubao wangu wa kazi? Kuna tani ya rasilimali zinazopatikana kwa kuajiri waandishi wa aina zote tofauti, pamoja na vidokezo kwa waandishi kupata wateja wanaotaka kulipa kile wanachostahili. Kwa kuongezea, ninafanya kazi ya kufanya ubao wangu wa kazi uwe mahali pazuri zaidi kwa waandishi, na wateja na waandishi wote wawili wanashiriki orodha hizo. Siwezi kufanya hivyo bila wewe, ingawa, hivyo kuangalia nje! Kwa kuongezea, ikiwa una maoni yoyote, maswali, au wasiwasi, daima ni huru zaidi kuacha wale katika sehemu ya maoni hapa chini. Ningependa kusikia maoni yako na ningekuwa na furaha zaidi kujibu maswali yako yoyote. Ni muhimu kushiriki habari ili kueneza ukweli. Watu wengi hawataki kufanya hivyo.