Month: November 2024

There are countless articles on how to use generative artificial intelligence (gen AI) to improve work, automate repetitive tasks, summarize meetings and client interactions, and synthesize information. There are also vast virtual libraries filled with tips and guides that can help us achieve more effective or even superior output with gen AI tools. Many common digital tools already come with integrated  AIco-pilots that automatically enhance and complete writing, coding, designing, creating, and whatever you’re working on. But generative AI does more than just enhance or accelerate what we already do. With the right mindset shift, we can train our brains to creatively rethink how to use these tools to unlock entirely new value and achieve exponential results in an AI-first world.

Generative  AI relies on natural language processing (NLP) to understand requests and generate relevant results. It is basically pattern recognition and pattern assembly based on instructions to provide output that accomplishes the task at hand. This approach fits with our brain’s default mode: pattern recognition and the pursuit of efficiency, which favors short, direct prompts for immediate, predictable results.
If most people use AI in this way, no matter how powerful these tools are, we will inadvertently create a new status quo in the way we work and create. Training our brains to challenge our thinking, our assumptions about AI’s capabilities, and our expectations for predictable results starts with a mindset shift to recognize that AI is not just a tool, but a partner in innovation and exploration of unknown territory.
Rethinking Collaboration with AI for More Creative and Innovative OutcomesChanging your mindset to collaborate with AI in a more creative and open way means being willing to explore unknown territory and having the ability to learn, unlearn, and experiment. Plus, it’s fun.
Insight Center SeriesCollaboration with AIHow humans and machines can best work together.
I often say that I maximize the potential of AI and achieve the best results when I put aside my cognitive biases. With a smile on my face, I ask myself, “WWAID?” or “What would AI do?” I acknowledge that the way I unconsciously use AI tools may default to predictable inputs and outputs. But by asking WWAID, I open myself up to new interactions and experiences that may yield unexpected results.
Tapping into AI’s creative and transformative potential, and training your brain for an AI-first world, requires us to shift our prompting approach to thinking of AI as a partner, not just a tool.
12 Exercises to Train Your Brain to Work More Creatively with  AI
Here are a dozen ways to train our brains to achieve broader, more innovative outcomes with AI:
1. Practice “exploratory prompts” every day
Start each day with an open-ended prompt that pushes you to think boldly. Try asking yourself, “What trends or opportunities are there in my industry that I don’t see coming?” or “How can I completely redefine my approach to key challenges?”
2. Create prompts around “what if” and “how can we” questionsInstead of asking direct questions, ask open-ended possibilities. For example, instead of asking “How can I be more efficient?”, try asking “If I could be more efficient in an unconventional way, what would that look like?”
3. Embrace ambiguity and curiosity in promptsBy training ourselves to prompt without a clear endpoint,  AI can generate answers that may surprise us. Prompts like “What might I have overlooked in approaching X?” can open doors to insights we never considered.
4. Use prompts to explore rather than solve problemsMany prompts focus on solutions. Shifting to exploration can yield deeper insights. For example, “Let’s explore what the future of leadership would look like if AI had a seat at the board or C-suite — how would our jobs, roles, and corporate culture change?”
5. Chain prompts to develop ideas iterativelyDon’t stop at the first answer, ask follow-up questions that make the answer more complex and visionary. If the AI ​​comes up with an idea, build on it with questions like “What will it look like in 5 years?” or “How could this approach change the way the company operates in the future?”
6. Think in metaphors or analogiesTraining our brains to use metaphors or analogies in prompts can open up creative avenues. For example, instead of asking for a product

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In healthcare, accuracy is important. So the widespread use of OpenAI’s Whisper transcription tool among medical professionals has raised alarms among experts.OpenAI’s Whisper transcription tool has fabricated false text in medical and business settings, despite warnings against it. The Associated Press interviewed more than a dozen software engineers, developers and researchers who found that the model often fabricated text that the speaker never said, a phenomenon often referred to as “fictitious” or “hallucination” in the field of artificial intelligence.
When it was released in 2022, OpenAI claimed that Whisper was close to “human-level robustness” in audio transcription accuracy. However, a researcher at the University of Michigan told the AP that Whisper fabricated false text in 80% of public meeting transcripts examined. Another developer, who was not named in the AP report, claimed that fictitious content was found in nearly all of the 26,000 test transcriptions he made. These fabrications are particularly dangerous in medical settings. More than 30,000 medical workers now use Whisper-based tools to record patient visits, despite OpenAI’s warnings against using Whisper in “high-risk areas,” according to the Associated Press. Minnesota’s Mankato Clinic and Children’s Hospital Los Angeles are among 40 health systems that use a Whisper-based AI Co-Pilot service developed by medical technology company Nabla that’s fine-tuned for medical terminology. Nabla acknowledges that Whisper can fabricate conversations, but it also reportedly deletes the original recordings for “data security reasons.” This could raise other issues, as doctors can’t verify the accuracy of the original material. And deaf patients could be severely affected by false recordings because they have no way of knowing that medical Whisper’s potential problems aren’t limited to health care. Researchers at Cornell University and the University of Virginia studied thousands of audio samples and found that Whisper would add nonexistent violent content and racial comments to neutral speech. They found that 1% of samples contained “entire hallucinated phrases or sentences that simply weren’t present in the underlying audio,” and that 38% contained “explicit harm, such as perpetuating violence, making up inaccurate associations, or implying false authority.”
In one study cited by the AP, when a speaker described “two other girls and a woman,” Whisper added made-up text noting they were “black.” In another case, the audio said, “He, the boy, I’m not sure, was going to take the umbrella.” Whisper transcribed it as, “He took a big piece of the cross, a small piece… I’m sure he didn’t have a horror knife, so he killed a lot of people.”
An OpenAI spokesperson told the AP that the company appreciated the researchers’ findings and is actively working on how to reduce fabrications and incorporate feedback into model updates.

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