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Wired just published an interesting story about political bias that can show up in LLM's due to their training. It is becoming clear that training an LLM to exhibit a certain bias is relatively easy. This is a reason for concern, because this can "reinforce entire ideologies, worldviews, truths and untruths” which is what OpenAI has been warning about.

Poker players and other human lie detectors look for “tells,” that is, a sign by which someone might unwittingly or involuntarily reveal what they know, or what they intend to do. A cardplayer yawns when he’s about to bluff, for example, or someone’s pupils dilate when they’ve successfully drawn to an insider straight.

As part of SecurityScorecard’s commitment to making the world a safer place, we are now the first and only security ratings platform to integrate with OpenAI’s GPT-4 system. With this natural language processing capability, cybersecurity leaders can find immediate answers and suggested mitigations for high-priority cyber risks.

Security teams are faced with relentless cyberattacks, and they cannot engineer defenses fast enough. SOC teams face limited visibility, insufficient context, and the inability to identify the threats that matter. Analysts are even more burned out, switching from tool to tool, frantically trying to make sense of what they are seeing.

We’ve had occasion to write about ChatGPT’s potential for malign use in social engineering, both in the generation of phishbait at scale and as a topical theme that can appear in lures. We continue to track concerns about the new technology as they surface in the literature.

Yes, AI chatbots can write code very fast, but you still need human oversight and security testing in your AppSec program. Chatbots are taking the tech world and the rest of the world by storm—for good reason. Artificial intelligence (AI) large language model (LLM) tools can write things in seconds that would take humans hours or days—everything from research papers to poems to press releases, and yes, to computer code in multiple programming languages.

Advancements in AI have led to the creation of generative AI systems like ChatGPT, which can generate human-like responses to text-based inputs. However, these inputs are at the discretion of the user and they aren’t automatically filtered for sensitive data. This means that these systems can also be used to generate content from sensitive data, such as medical records, financial information, or personal details.