Responsible AI Collaborative’s Post

On the hunt for the perfect adverse media screening tool? Dive into our comparison guide. ⚠️👀 https://okt.to/gbrA5a

This the fourth and last post written by my colleague Carl Robinson and me where we share different use cases for deep search and how this approach can effectively extract value and insights from data that is not always readily available.

The final article of Volume 30 is here! In this article, “Internet Openness at Risk: Generative AI’s Impact on Data Scraping,” Melany Amarikwa examines recent cases involving the scraping of user data for generative AI models. She proposes a flexible framework to allow innovative uses of publicly available data while protecting individual privacy and property rights.   On behalf of the members of Volume 30, we thank you for being part of our community. The completion of this Volume marks the end of one era and the beginning of a new one. We look forward to experiencing the next 30 years of JOLT with you all! #techlaw #privacylaw #propertylaw #datascraping #data #dataprivacy #generativeAI

Is your data standing in the way of your risk response? Are you always trying to track down the most recent figures you need to make good decisions? Then your data isn't working for you. Find out how ClearDox's intelligent applications can change that in our recent blog post. https://hubs.li/Q02DCNDF0

LOTS of interesting and good discussions about this business imperative to "Own Your Own Intelligence" started by a very early draft blog post Please keep sharing feedback. John Sviokla and I are working on an update with more specifics for discussion https://lnkd.in/eXYYis-w

A lot of great words in here, including some I hadn't heard of—like #CIB, "Coordinated Inauthentic Behavior," which refers to a systematic effort across thousands of fake accounts to create the appearance of a groundswell of grassroots support for a position or cause when none actually exists. Although it's valuable to have a precise vocabulary to name and describe phenomena, it's equally important to understand when something is a genuinely new and distinct phenomenon and when it is just the same tired old pig dressed up in different clothes. If you believe, for example, that you could generally trust what governments and institutions told you forty or fifty years ago, but you have trouble believing so today, you either lived a very charmed life when you were younger or you are remembering it very poorly. Whether it is in the racist overtones of the multi-decade disinformation campaign against cannabis, or in the whole-cloth fabrication of the "Welfare Queen" archetype in the 1976 Presidential race, it is impossible to point to a time in our lives where we haven't been influenced by deliberate and widespread #malinformation or when we have been particularly good at inoculating the body politic against it. This is not to say that the #democratization of #AI doesn't present unique challenges to society in putting weapons-grade #disinformation into the hands of nearly anyone inclined to use it. It is one thing to say, after all, that humanity should take heart that it has not destroyed itself in the years since the capacity to explode a nuclear weapon spread from one country to nine; it would be quite another to say that we should extend that sense of comfort to a hypothetical world in which 9 billion people each had control of a few tactical nuclear weapons in their own backyards. To some degree, the capacity for anyone to create a believable, fictitious narrative about anything is an alarming development in the arms race against political manipulation, character assassination, and identity theft. At the same time, the capacity for anyone to use the same tools to track, unmask, disempower, and sterilize deliberate falsehoods has never existed to this extent in the past either. What was once the realm of heroics of dedicated people like Pamela Jones and #Groklaw is now available—through tireless #AI agents and open data sources—to everyone. When Stephen Colbert coined the term #truthiness in 2005 to mock the human susceptibility to arguments that "feel" true even when they are actually not true, there was already a widely-used word in English to describe exactly the same thing: #speciousness. It's been part of the English lexicon for more than 500 years. We've survived, by and large, in an uneasy truce with #falsehood for all that time. Perhaps now is the time we win.

In the age of rampant online disinformation, preserving truth requires advanced tools. Web scraping helps combat online fake news by automating data collection and monitoring. This tool is essential for preserving accurate information in the digital age. Vaidotas Sedys from Oxylabs.io shares his insights ⤵️ 🔗: https://lnkd.in/gax5dr5G #Disinformation #WebScraping #InformationSecurityBuzz

An Overview of the Data-Loader Landscape: Discussion ... https://lnkd.in/ezGSaFZK #AI #ML #Automation

An insight into the the future of intelligence, blending the Analyst Craft with the advantages of AI capability. Allowing the highly experienced teams of Analysts to work with unstructured data sets on a truly massive scale for today and embrace the ability to scale for the future.

Part two of my two part article on multi-agency, enumerating what I see as pitfalls and corresponding mitigations. I'd love to hear your thoughts on these topics, especially first-hand experiences and challenges you may have encountered on the path to multi-agent systems.