It’s come to be a widely-accepted truth that AI is on its way to removing thousands, if not millions, jobs – but for experts who make decisions, incorporating numerous contextual factors, this will probably not be the case. AI will be relevant for experts to augment their capabilities (Intelligence Augmentation) rather replace through complete automation (Artificial Intelligence). What kind of experts? Doctors, teachers, journalists and not least Cybersecurity analysts.
Frank Pasquale, in his book New Laws of Robotics – Defending Human Expertise in the Age of AI (2020), shares how firms “with the most to gain from AI”, such as IBM, shifted gears to focus on IA over AI. For example: “IBM has shifted the marketing of its Watson system in health care and law, billing it as more of a helper for than a replacement of doctors… they promote a vision of augmented, not artificial, intelligence.” (35). Applicable beyond the medical domain, Pasquale writes: “the dream of a wholly automated diagnostic tool may soon seem more anachronistic than futuristic.”
Penfield.AI’s team couldn’t agree more with Pasquale when it comes to Cybersecurity analysts in Security Operation Centers (SOC): we’re in the space of Intelligence Automation (IA) for analysts in SOCs by using AI to upskill people in real-time.
Why IA? Cybersecurity threats are dynamic because of the sophisticated malicious actors constantly upping their game. To resolve dynamic Cybersecurity threats efficiently and accurately, analysts ingest many contextual factors under pressure. Not only is there room to become more efficient and accurate, but there is also an opportunity to reduce burn-out among analysts. To alleviate the pressure, Penfield.AI’s tool was developed, reducing time to resolve threats by roughly 38%.
Can you think of examples of where AI is better used for Intelligence Augmentation over complete automation? Share in the comments!
