If you're struggling to use ChatGPT and other AI tools in the office, you may be falling into one of three big "gaps" in effective AI implementation. Find out how to close these gaps, and catch up on other AI-related news, in this week's roundup from Advisory Board's Thomas Seay.
In these early days of the AI era, many companies are simply giving their employees access to AI tools and hoping for the best. But in a recent post to his always-interesting blog One Useful Thing, Ethan Mollick, an associate professor at The Wharton School, argues that we'll achieve the biggest gains from AI only after we fundamentally reshape the culture and methodology of work.
To which you might be saying: OK, sure, let's rewire work for AI … but, um, how?
Mollick offers a few ideas, such as using AI to summarize stakeholder feedback, but it's worth taking a step back to view the bigger picture. How do our current work practices inhibit the use of AI? And how might we overcome those obstacles?
I'd flag three key gaps that managers can tackle right now: what I'll call the access gap, the ignorance gap, and the consistency gap.
The Access Gap. Many employees are still barred entirely from AI tools. Sometimes, these prohibitions exist for very good reasons (for instance, most AI tools aren't approved for HIPAA-protected data), but other times, they stem from overblown fears of AI's risks.
The Ignorance Gap. Most people simply don't know how to use AI effectively. That's no surprise: These tools barely existed a year ago, and few people have received formal education on how to use them.
The Consistency Gap. Even when people do know how to use AI, they may neglect to use it regularly, especially if their work habits have been ingrained by long practice. I fall into this trap all the time: For instance, I know AI tools are great at summarizing my virtual meetings from their transcripts … but I often forget to turn on transcription anyway.
In the longer term, as Mollick points out, we'll all have more work to do to fully integrate AI into our offices. We'll need to build AI tools into all of our software, restructure teams to make better use of AI, and more.
But you don’t have to wait. You can start closing the access, ignorance, and consistency gaps right now.
Large language models (LLMs) can do much more than chat. Because ChatGPT kicked off the current AI craze, many people tend to think of LLMs as just "chatbots." But in truth, LLMs are a new form of intelligence that you can use in many ways. This post describes an LLM-powered "Research Assistant" that takes a query, breaks it down into subcomponent questions, performs the necessary research, and drafts a final response. The multi-step process is much slower than just asking a question to ChatGPT, but in many use cases, speed matters less than accuracy and comprehensiveness.
A technical (but really good!) one-hour intro to LLMs. If you're ready to dive deeper into the underlying workings of LLMs, this YouTube video from OpenAI's Andrej Karpathy is a great resource, covering everything from technical fundamentals to security implications. (If you'd rather just skim the slide deck, that's available too.)
Is "artificial general intelligence" already here? Many pioneers of the AI age have defined their holy grail as achieving "AGI," or artificial general intelligence. OpenAI's mission statement, for instance, is "to ensure that artificial general intelligence benefits all of humanity." But what if AGI is already here? This article from Noema argues that "[d]ecades from now, [tools such as ChatGPT] will be recognized as the first true examples of AGI, just as the 1945 ENIAC is now recognized as the first true general-purpose electronic computer."
Your life, as narrated by David Attenborough. In a wild sign of things to come, a developer has tied his webcam to an AI voice generator that narrates his day-to-day life in the distinctive voice of David Attenborough: "Here we have a remarkable specimen of homo sapiens, distinguished by his remarkable silver spectacles and a mane of tousled curly locks." (Sadly, the real-life David Attenborough finds this "personally distressing.")
Artificial intelligence (AI) can provide innovative solutions to some of healthcare's greatest problems, but only if we address associated obstacles and risks. Explore five AI challenges and get actionable solutions to help your organization overcome them.
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