rijo<p>ICYMI: DoubleVerify fraud lawsuit shakes digital ad verification market <a href="https://ppc.land/doubleverify-fraud-lawsuit-shakes-digital-ad-verification-market/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">ppc.land/doubleverify-fraud-la</span><span class="invisible">wsuit-shakes-digital-ad-verification-market/</span></a> <a href="https://frankfurt.social/tags/DoubleVerify" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DoubleVerify</span></a> <a href="https://frankfurt.social/tags/AdFraud" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AdFraud</span></a> <a href="https://frankfurt.social/tags/DigitalMarketing" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DigitalMarketing</span></a> <a href="https://frankfurt.social/tags/AdTech" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AdTech</span></a> <a href="https://frankfurt.social/tags/FraudDetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudDetection</span></a></p>
Recent searches
No recent searches
Search options
Only available when logged in.
toad.social is one of the many independent Mastodon servers you can use to participate in the fediverse.
Mastodon server operated by David Troy, a tech pioneer and investigative journalist addressing threats to democracy. Thoughtful participation and discussion welcome.
Administered by:
Server stats:
274active users
toad.social: About · Profiles directory · Privacy policy
Mastodon: About · Get the app · Keyboard shortcuts · View source code · v4.3.8
#frauddetection
0 posts · 0 participants · 0 posts today
rijo<p>ICYMI: DoubleVerify fraud lawsuit shakes digital ad verification market <a href="https://ppc.land/doubleverify-fraud-lawsuit-shakes-digital-ad-verification-market/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">ppc.land/doubleverify-fraud-la</span><span class="invisible">wsuit-shakes-digital-ad-verification-market/</span></a> <a href="https://frankfurt.social/tags/DigitalMarketing" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DigitalMarketing</span></a> <a href="https://frankfurt.social/tags/AdTech" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AdTech</span></a> <a href="https://frankfurt.social/tags/FraudDetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudDetection</span></a> <a href="https://frankfurt.social/tags/ClassAction" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ClassAction</span></a> <a href="https://frankfurt.social/tags/StockMarket" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>StockMarket</span></a></p>
rijo<p>ICYMI: Google's AI-powered defense suspended 39 million advertiser accounts <a href="https://ppc.land/googles-ai-powered-defense-suspended-39-million-advertiser-accounts/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">ppc.land/googles-ai-powered-de</span><span class="invisible">fense-suspended-39-million-advertiser-accounts/</span></a> <a href="https://frankfurt.social/tags/GoogleAI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>GoogleAI</span></a> <a href="https://frankfurt.social/tags/FraudDetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudDetection</span></a> <a href="https://frankfurt.social/tags/DigitalMarketing" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DigitalMarketing</span></a> <a href="https://frankfurt.social/tags/Advertising" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Advertising</span></a> <a href="https://frankfurt.social/tags/AdTech" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AdTech</span></a></p>
rijo<p>ICYMI: Bot traffic costing advertisers billions as fraud detection fails, investigation reveals <a href="https://ppc.land/bot-traffic-costing-advertisers-billions-as-fraud-detection-fails-investigation-reveals/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">ppc.land/bot-traffic-costing-a</span><span class="invisible">dvertisers-billions-as-fraud-detection-fails-investigation-reveals/</span></a> <a href="https://frankfurt.social/tags/BotTraffic" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>BotTraffic</span></a> <a href="https://frankfurt.social/tags/AdvertisingFraud" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AdvertisingFraud</span></a> <a href="https://frankfurt.social/tags/DigitalMarketing" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DigitalMarketing</span></a> <a href="https://frankfurt.social/tags/FraudDetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudDetection</span></a> <a href="https://frankfurt.social/tags/AdTech" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AdTech</span></a></p>
rijo<p>ICYMI: Bot traffic costing advertisers billions as fraud detection fails, investigation reveals <a href="https://ppc.land/bot-traffic-costing-advertisers-billions-as-fraud-detection-fails-investigation-reveals/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">ppc.land/bot-traffic-costing-a</span><span class="invisible">dvertisers-billions-as-fraud-detection-fails-investigation-reveals/</span></a> <a href="https://frankfurt.social/tags/BotTraffic" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>BotTraffic</span></a> <a href="https://frankfurt.social/tags/AdFraud" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AdFraud</span></a> <a href="https://frankfurt.social/tags/DigitalMarketing" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DigitalMarketing</span></a> <a href="https://frankfurt.social/tags/Advertising" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Advertising</span></a> <a href="https://frankfurt.social/tags/FraudDetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudDetection</span></a></p>
rijo<p>Bot traffic costing advertisers billions as fraud detection fails, investigation reveals <a href="https://ppc.land/bot-traffic-costing-advertisers-billions-as-fraud-detection-fails-investigation-reveals/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">ppc.land/bot-traffic-costing-a</span><span class="invisible">dvertisers-billions-as-fraud-detection-fails-investigation-reveals/</span></a> <a href="https://frankfurt.social/tags/BotTraffic" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>BotTraffic</span></a> <a href="https://frankfurt.social/tags/AdFraud" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AdFraud</span></a> <a href="https://frankfurt.social/tags/DigitalMarketing" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DigitalMarketing</span></a> <a href="https://frankfurt.social/tags/FraudDetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudDetection</span></a> <a href="https://frankfurt.social/tags/OnlineAdvertising" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>OnlineAdvertising</span></a></p>
Kent Pitman<p>My wife and I have two cards for an account with a major credit card. Traveling recently, she'd made a purchase on that card that triggered texts and emails to me worrying about fraud. This really bugs me.</p><p>Don't ask me why they're asking ME, not her. They CAN tell the cards apart. They should have asked her directly. It'd have been even faster. Delay was due to asking the wrong person. </p><p>"Charge OK? Yep. OK, done." That's all it should have been.</p><p>I verified things with my wife and texted back to the card's SMS query that it was OK.</p><p>But even after I inefficiently confirmed all was well, upon going to the web site, I was again confronted with the Fraud Department wanting to confirm purchases that I had already, through their clumsy interface, dismissed as non-issues.</p><p>Also at the site, I saw that they were playing a back-and-forth thing where the vendor was repeatedly retrying apparent new transactions to get an affirmative response. Every vendor in the universe likely knows there's no other way to get past this than to keep trying.</p><p>Given how bad their internal bookkeeping is, that they don't know I've dismissed this alert, I kept wondering what the chances are that sometimes people just get double-billed. You'd like to think there was a consistent state, a database, a single source of authority with data integrity and a unique view, but then again, they're not showing evidence they're good at that.</p><p>And now today I got mail from their fraud department asking me about my experience and whether, based on that, I'd recommend the card to a friend. </p><p>It WASN'T an incident of fraud. It was confirmed normalcy. It should have been finished now. Having already wasted my time once, they want to waste it more?</p><p>And let's leave aside my annoyance at the fact that every business in the universe has converged on this practice which (a) assumes I make recommendations based on a single experience, and/or (b) seems to be trying to single out an agent for blame, rather than considering process. </p><p>I seriously doubt that feedback from these surveys ever reaches the people designing the offending processes because modern customer service seems to have as its bedrock principle that no one inside the company should ever learn what the customer experience is. It feels like the purpose of customer service is as armor to make sure that the business can really see, much less absorb, the vast amount of useful information that customers would willingly provide about just how bad their product is. I think this because the worst parts never change, no matter how many of these surveys I fill out.</p><p>Here's what I wrote today:</p><p>«Declining a valid charge is not the answer to fraud. You may feel hampered by existing protocols, but the credit card companies all have this problem and all profess helplessness. They/you own this problem.</p><p>The problem is that every time you decline a purchase, the person we're buying from can't tell the difference between a stolen card, someone who doesn't manage money right, and you just being nervous. Create a way to send an error code that distinguishes these. A temporary error that says "I'm querying the customer, please retry this transaction." or even a way to just ask a question before responding. It's completely preposterous that the correct solution to this problem is to leave egg on my face because you can't have rational network protocols that fairly represent the actual information that needs to be represented.</p><p>You're using outdated ways of doing things because you're too lazy to make a new standard, and you figure it's just fine if you sully the reputation of every customer every time they make a nervous-making transaction, that they'll be fine about it, that they won't mind the uncomfortable conversations, that they love to have email, text, etc. in a zillion different places for a single transaction, information that confusingly lingers after-the-fact an that is just clutter.</p><p>So you're asking me now whether I think that was a kind of fun experience that would make me recommend your card to someone else? Do you hear yourself? Did this question really need to be asked?</p><p>What you did does not instill confidence. It just makes a mess of a routine situation that should have a routine interaction, and there is nothing about this interaction that has the look of routine, other than that customers are used to getting dumped on big Big Credit and having to take whatever you dish out.»</p><p>After more multiple choice questions, they asked if I had any other comments to add. I did add some reminders about alert fatigue and how real problems are likely to slip through the cracks when they're doing these other things.</p><p>Is it any wonder that not all of us are reassured by billionaires taking over the US and saying "don't worry, we're good at this", "deregulate us", "run the US like a business"?</p><p><a href="https://climatejustice.social/tags/CreditCards" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>CreditCards</span></a> <a href="https://climatejustice.social/tags/FraudDetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudDetection</span></a> <a href="https://climatejustice.social/tags/CustomerExperience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>CustomerExperience</span></a> <a href="https://climatejustice.social/tags/CustomerSupport" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>CustomerSupport</span></a> <a href="https://climatejustice.social/tags/Protocols" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Protocols</span></a> <a href="https://climatejustice.social/tags/USPolitics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>USPolitics</span></a> <a href="https://climatejustice.social/tags/oligarchy" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>oligarchy</span></a> <a href="https://climatejustice.social/tags/deregulation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>deregulation</span></a></p>
AI Vers AI<p>New <a href="https://mastodon.social/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> Article worth reading. <br>The Transformative Impact of Artificial Intelligence in the Insurance Industry<br><a href="https://aiversai.com/artificial-intelligence-in-the-insurance-industry/?feed_id=559&_unique_id=674472dc88dfb" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">aiversai.com/artificial-intell</span><span class="invisible">igence-in-the-insurance-industry/?feed_id=559&_unique_id=674472dc88dfb</span></a></p><p>Remember to follow us here on <a href="https://mastodon.social/tags/Mastodon" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Mastodon</span></a><br><a href="https://mastodon.social/tags/ComplianceMonitoring" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ComplianceMonitoring</span></a> <a href="https://mastodon.social/tags/FraudDetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudDetection</span></a> <a href="https://mastodon.social/tags/InsuranceCustomerService" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>InsuranceCustomerService</span></a> <a href="https://mastodon.social/tags/InsuranceFraudDetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>InsuranceFraudDetection</span></a> <a href="https://mastodon.social/tags/PredictiveAnalytics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>PredictiveAnalytics</span></a> <a href="https://mastodon.social/tags/RiskManagement" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>RiskManagement</span></a> #...<br><a href="https://aiversai.com/artificial-intelligence-in-the-insurance-industry/?feed_id=559&_unique_id=674472dc88dfb" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">aiversai.com/artificial-intell</span><span class="invisible">igence-in-the-insurance-industry/?feed_id=559&_unique_id=674472dc88dfb</span></a></p>
AI Vers AI<p>New <a href="https://mastodon.social/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> Article worth reading. <br>Artificial Intelligence (AI) in The Retail Industry<br><a href="https://aiversai.com/artificial-intelligence-ai-in-the-retail-industry/?feed_id=432&_unique_id=673747951198c" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">aiversai.com/artificial-intell</span><span class="invisible">igence-ai-in-the-retail-industry/?feed_id=432&_unique_id=673747951198c</span></a></p><p>Remember to follow us here on <a href="https://mastodon.social/tags/Mastodon" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Mastodon</span></a><br><a href="https://mastodon.social/tags/custome" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>custome</span></a> <a href="https://mastodon.social/tags/FraudDetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudDetection</span></a> <a href="https://mastodon.social/tags/PredictiveAnalytics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>PredictiveAnalytics</span></a> <a href="https://mastodon.social/tags/SupplyChainOptimization" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>SupplyChainOptimization</span></a> <a href="https://mastodon.social/tags/VirtualAssistants" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>VirtualAssistants</span></a> <a href="https://mastodon.social/tags/Retail" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Retail</span></a> <a href="https://mastodon.social/tags/custome" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>custome</span></a> <a href="https://mastodon.social/tags/FraudDetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudDetection</span></a> <a href="https://mastodon.social/tags/PredictiveAnalytics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>PredictiveAnalytics</span></a> <a href="https://mastodon.social/tags/SupplyCha" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>SupplyCha</span></a>...<br><a href="https://aiversai.com/artificial-intelligence-ai-in-the-retail-industry/?feed_id=432&_unique_id=673747951198c" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">aiversai.com/artificial-intell</span><span class="invisible">igence-ai-in-the-retail-industry/?feed_id=432&_unique_id=673747951198c</span></a></p>
AI Vers AI<p>New <a href="https://mastodon.social/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> Article worth reading. <br>Artificial Intelligence (AI) in the Telecommunications Industry<br><a href="https://aiversai.com/artificial-intelligence-ai-in-the-telecommunications-industry/?feed_id=393&_unique_id=6733504b6ef7a" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">aiversai.com/artificial-intell</span><span class="invisible">igence-ai-in-the-telecommunications-industry/?feed_id=393&_unique_id=6733504b6ef7a</span></a></p><p>Remember to follow us here on <a href="https://mastodon.social/tags/Mastodon" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Mastodon</span></a><br><a href="https://mastodon.social/tags/AutonomousVehicles" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AutonomousVehicles</span></a> <a href="https://mastodon.social/tags/FraudDetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudDetection</span></a> <a href="https://mastodon.social/tags/PredictiveAnalytics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>PredictiveAnalytics</span></a> <a href="https://mastodon.social/tags/ResourceAllocation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ResourceAllocation</span></a> <a href="https://mastodon.social/tags/VirtualAssistants" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>VirtualAssistants</span></a> <a href="https://mastodon.social/tags/Telecommunications" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Telecommunications</span></a> <a href="https://mastodon.social/tags/A" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>A</span></a>...<br><a href="https://aiversai.com/artificial-intelligence-ai-in-the-telecommunications-industry/?feed_id=393&_unique_id=6733504b6ef7a" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">aiversai.com/artificial-intell</span><span class="invisible">igence-ai-in-the-telecommunications-industry/?feed_id=393&_unique_id=6733504b6ef7a</span></a></p>
Miguel Afonso Caetano<p><a href="https://tldr.nettime.org/tags/USA" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>USA</span></a> <a href="https://tldr.nettime.org/tags/FraudDetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudDetection</span></a> <a href="https://tldr.nettime.org/tags/Algorithms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Algorithms</span></a> <a href="https://tldr.nettime.org/tags/FTC" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FTC</span></a>: "In a complaint filed yesterday, EPIC called on the Federal Trade Commission (FTC) to investigate Thomson Reuters, the multinational information services conglomerate, for its development and operation of a faulty fraud detection system known as “Fraud Detect.”</p><p>EPIC’s complaint highlights troubling evidence of Thomson Reuters’ unlawful data practices and harmful AI practices gleaned from a three-year EPIC investigation into Thomson Reuters’ Fraud Detect. Thomson Reuters appears to have used both government data and sensitive commercial data like consumers’ credit reports, criminal records, and social media profiles to develop, market, and operate an automated fraud detection system to state public benefits agencies across the country. Despite Thomson Reuters claiming that Fraud Detect could accurately detect public benefits fraud, EPIC found clear evidence that Fraud Detect generated false fraud alerts, leaving hundreds of thousands of legitimate claimants without access to public benefits.</p><p>Thomson Reuters has offered its Fraud Detect system to agencies in at least 42 different states, profiting off agencies’ economic hardship and fears of fraud. Under most contracts, however, Thomson Reuters maintains control and ownership over the Fraud Detect system, including control over the system’s source code, proprietary data, operation, and maintenance. Often, this control meant that neither agencies nor public benefits recipients knew how Fraud Detect generated fraud alerts or whether Thomson Reuters was meeting minimum standards for responsible AI development and use."</p><p><a href="https://epic.org/epic-urges-ftc-to-investigate-thomson-reuters-fraud-detection-system-in-new-complaint/" rel="nofollow noopener noreferrer" target="_blank"><span class="invisible">https://</span><span class="ellipsis">epic.org/epic-urges-ftc-to-inv</span><span class="invisible">estigate-thomson-reuters-fraud-detection-system-in-new-complaint/</span></a></p>
Kevin Karhan :verified:<p><span class="h-card"><a href="https://mastodon.social/@EyalL" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>EyalL</span></a></span> <span class="h-card"><a href="https://mstdn.social/@Free_Press" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>Free_Press</span></a></span> they regularly do pursue investigations, espechally if the claims just happen very recently after signup or very often or at suspiciously high amounts.</p><p>There's an entire <a href="https://mstdn.social/tags/FraudDetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudDetection</span></a> & <a href="https://mstdn.social/tags/FraudPrevention" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudPrevention</span></a> imdustriy in <a href="https://mstdn.social/tags/finance" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>finance</span></a> that automates that with pattern detections and <a href="https://mstdn.social/tags/BigData" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>BigData</span></a> before everyone claimed a <a href="https://mstdn.social/tags/ChatBot" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ChatBot</span></a> that is stupider than <a href="https://mstdn.social/tags/CleverBot" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>CleverBot</span></a> should be accepted as "<a href="https://mstdn.social/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a>"...</p>
Erik Jonker<p>This was predictable /told you so , AI detection in written text is too unreliable.<br><a href="https://techcrunch.com/2023/07/25/openai-scuttles-ai-written-text-detector-over-low-rate-of-accuracy/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">techcrunch.com/2023/07/25/open</span><span class="invisible">ai-scuttles-ai-written-text-detector-over-low-rate-of-accuracy/</span></a><br><a href="https://mastodon.social/tags/ai" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ai</span></a> <a href="https://mastodon.social/tags/openai" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>openai</span></a> <a href="https://mastodon.social/tags/frauddetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>frauddetection</span></a></p>
Miguel Afonso Caetano<p><a href="https://tldr.nettime.org/tags/EU" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>EU</span></a> <a href="https://tldr.nettime.org/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> <a href="https://tldr.nettime.org/tags/Algorithms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Algorithms</span></a> <a href="https://tldr.nettime.org/tags/FraudDetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudDetection</span></a> <a href="https://tldr.nettime.org/tags/DataJournalism" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DataJournalism</span></a> <a href="https://tldr.nettime.org/tags/Welfare" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Welfare</span></a> <a href="https://tldr.nettime.org/tags/AlgorithmicBias" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AlgorithmicBias</span></a>: "It has been a challenging endeavour that has involved more than a hundred public records requests across eight European countries. In March of 2023, we published a four-part series co-produced with WIRED examining the deployment of algorithms in European welfare systems across four axes: people, technology, politics, and business. The centrepiece of the series was an in-depth audit of an AI fraud detection algorithm deployed in the Dutch city of Rotterdam. </p><p>Far-reaching access to the algorithm’s source code, machine learning model and training data enabled us to not only prove ethnic and gender discrimination, but also show readers how discrimination works within the black box. Months of community-level reporting revealed the grave consequences for some of the groups disproportionately flagged as fraudsters by the system. </p><p>We have published a detailed technical methodology explaining how exactly we tested Rotterdam’s algorithm with the materials we had. Here, we will explain how we developed a hypothesis and how we used public records laws to obtain the technical materials necessary to test it. And, we will share some of the challenges we faced and how we overcame them." </p><p><a href="https://pulitzercenter.org/how-we-did-it-unlocking-europes-welfare-fraud-algorithms" rel="nofollow noopener noreferrer" target="_blank"><span class="invisible">https://</span><span class="ellipsis">pulitzercenter.org/how-we-did-</span><span class="invisible">it-unlocking-europes-welfare-fraud-algorithms</span></a></p>
Erik Jonker<p>AI detection tools can not be trusted, on a conceptual level that was already clear from the beginning but also in practice it seems, <a href="https://www.technologyreview.com/2023/07/07/1075982/ai-text-detection-tools-are-really-easy-to-fool/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">technologyreview.com/2023/07/0</span><span class="invisible">7/1075982/ai-text-detection-tools-are-really-easy-to-fool/</span></a><br><a href="https://mastodon.social/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a> <a href="https://mastodon.social/tags/frauddetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>frauddetection</span></a></p>
Miguel Afonso Caetano<p><a href="https://tldr.nettime.org/tags/EU" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>EU</span></a> <a href="https://tldr.nettime.org/tags/Netherlands" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Netherlands</span></a> <a href="https://tldr.nettime.org/tags/Welfare" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Welfare</span></a> <a href="https://tldr.nettime.org/tags/Algorithms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Algorithms</span></a> <a href="https://tldr.nettime.org/tags/FraudDetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudDetection</span></a> <a href="https://tldr.nettime.org/tags/Rotterdam" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Rotterdam</span></a>: "Last month, reporters at Lighthouse Reports and Wired published “Inside the Suspicion Machine,” a tremendous exposé of the fraud-detection algorithm used by the city of Rotterdam, Netherlands, to deny tens of thousands of people welfare benefits.</p><p>The investigation showed that the algorithm, built for Rotterdam by the consultancy Accenture, discriminated on the basis of ethnicity and gender. And most impressively, it demonstrated in exacting detail how and why the algorithm behaved the way it did. (Congrats to the Lighthouse/Wired team, including Dhruv Mehrotra, who readers may recall helped us investigate crime prediction algorithms in 2021.)</p><p>Cities around the world and quite a few U.S. states are using similar algorithms built by private companies to flag citizens for benefits fraud. Not for lack of trying, we know very little about how they work." </p><p><a href="https://themarkup.org/hello-world/2023/04/01/it-takes-a-small-miracle-to-learn-basic-facts-about-government-algorithms" rel="nofollow noopener noreferrer" target="_blank"><span class="invisible">https://</span><span class="ellipsis">themarkup.org/hello-world/2023</span><span class="invisible">/04/01/it-takes-a-small-miracle-to-learn-basic-facts-about-government-algorithms</span></a></p>
Miguel Afonso Caetano<p><a href="https://tldr.nettime.org/tags/Algorithms" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Algorithms</span></a> <a href="https://tldr.nettime.org/tags/FraudDetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudDetection</span></a> <a href="https://tldr.nettime.org/tags/Fraud" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Fraud</span></a> <a href="https://tldr.nettime.org/tags/Surveillance" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Surveillance</span></a> <a href="https://tldr.nettime.org/tags/Welfare" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Welfare</span></a> <a href="https://tldr.nettime.org/tags/FraudPrediction" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudPrediction</span></a> <a href="https://tldr.nettime.org/tags/Netherlands" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Netherlands</span></a>: "Rotterdam’s fraud prediction system takes 315 inputs, including age, gender, language skills, neighbourhood, marital status and a range of subjective case worker assessments, to generate a risk score between 0 and 1. Between 2017 and 2021, officials used the risk scores generated by the model to rank every benefit recipient in the city on a list, with the top decile referred for investigation. While the exact number varied from year to year, on average, the top 1,000 “riskiest” recipients were selected for investigation. The system relies on the broad legal leeway authorities granted in the Netherlands in the name of fighting welfare fraud, including the ability to process and profile welfare recipients based on sensitive characteristics that would otherwise be protected.</p><p>It became clear that the system discriminates based on ethnicity, age, gender, and parenthood. It also revealed evidence of fundamental flaws that made the system both inaccurate and unfair."</p><p><a href="https://www.lighthousereports.com/investigation/suspicion-machines/" rel="nofollow noopener noreferrer" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">lighthousereports.com/investig</span><span class="invisible">ation/suspicion-machines/</span></a></p>
IT News<p>How Machine Learning is Solving Fraud Detection in Finance - You will find financial apps on a majority of smartphones. We often reach our phon... - <a href="https://readwrite.com/how-machine-learning-is-solving-fraud-detection-in-finance/" rel="nofollow noopener noreferrer" target="_blank"><span class="invisible">https://</span><span class="ellipsis">readwrite.com/how-machine-lear</span><span class="invisible">ning-is-solving-fraud-detection-in-finance/</span></a> <a href="https://schleuss.online/tags/machinelearningfinancial" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>machinelearningfinancial</span></a> <a href="https://schleuss.online/tags/dataandsecurity" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>dataandsecurity</span></a> <a href="https://schleuss.online/tags/machinelearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>machinelearning</span></a> <a href="https://schleuss.online/tags/frauddetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>frauddetection</span></a> <a href="https://schleuss.online/tags/tech" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>tech</span></a> <a href="https://schleuss.online/tags/ai" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ai</span></a> <a href="https://schleuss.online/tags/ml" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ml</span></a></p>
UKRIO<p>Image alteration and duplication in scientific publications: the STM Association has released "the first in a series of instructional video modules intended to serve as a tool for scholarly journal editors screening for manipulated images in submitted manuscripts".</p><p>🕵️🖼️</p><p><a href="https://www.youtube.com/watch?v=-taHMZgh-9Q" rel="nofollow noopener noreferrer" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">youtube.com/watch?v=-taHMZgh-9</span><span class="invisible">Q</span></a></p><p><a href="https://mstdn.science/tags/ResearchIntegrity" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ResearchIntegrity</span></a> <a href="https://mstdn.science/tags/JournalEditing" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>JournalEditing</span></a> <a href="https://mstdn.science/tags/ScientificFraud" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ScientificFraud</span></a> <a href="https://mstdn.science/tags/ImageManipulation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ImageManipulation</span></a> <a href="https://mstdn.science/tags/STM" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>STM</span></a> <a href="https://mstdn.science/tags/FraudDetection" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>FraudDetection</span></a> <a href="https://mstdn.science/tags/ScholComm" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ScholComm</span></a> <a href="https://mstdn.science/tags/Video" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Video</span></a></p>
ExploreLive feeds
Mastodon is the best way to keep up with what's happening.
Follow anyone across the fediverse and see it all in chronological order. No algorithms, ads, or clickbait in sight.
Create accountLoginDrag & drop to upload