AI co-pilots/virtual assistants impact human critical thinking.
As I mentioned in my previous article , Artificial intelligence (AI) has come a long way in recent years. AI is making a significant impact in supporting human decision-making, with the development of AI co-pilots or virtual assistants. While these technologies offer many benefits, they also raise important questions about their impact on critical thinking.
AI co-pilots and virtual assistants are designed to support human decision making across various tasks. For example, AI co-pilots can provide developers with suggestions on coding, build test cases for testers, provide summaries of financial advice for financial advisors or create summaries of research papers for researchers.
One of the main advantages of AI co-pilots or virtual assistants is that they can help reduce the workload on humans, allowing them to focus on other critical or creative tasks. Releasing the human element to make critical decisions applying all the senses of intelligence to a problem domain or being creative.
However, the increasing use of AI co-pilots and virtual assistants also raises concerns about the impact on critical thinking. In particular, some experts worry that relying too heavily on AI may reduce human decision-making skills, especially in high-pressure or high-impact situations.
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To address these concerns, it is essential to strike a balance between the use of AI and human decision-making skills. AI co-pilots and virtual assistants should be designed to support, rather than replace, humans. This means that humans should remain in control of critical decision-making tasks and that AI should be used to augment their abilities, rather than replace them, the responsibility remains with the human interaction and we must remember to remain alert. Too often we have seen measures in technology to automate processes and prompt when making critical decisions to ensure human step-in oversight. This has been seen in the past with providing prompts for input before proceeding or changing the colour of screens to attract attention. Over time humans become blind to these prompts and just accept. It will be important to switch up these prompts as AI co-pilots or virtual assistants provide more and more input to our decision-making, this is especially important when it impacts individuals or communities outside of the decision making.
Growing usage of AI co-pilot/virtual assistants is inevitable and will work its way into every aspect of technology, industry and business. It is crucial to strike a balance between the use of AI and human decision-making skills. By designing these technologies to support, rather than replace, humans it should enhance your businesses.
Whilst the technology is complex, the ethical and governance around AI usage is more important to get right in the initial steps than the techn;ogy development. If you have the time, read the responsibility statements by the following technology companies and build on this work within your business.
Chief Happiness Officer @ Smiling Bowtie | I help tech leaders use happiness as a competitive advantage to increase engagement and fulfillment | Workplace Happiness Expert | Keynote Speaker & Leadership Coach
1 年Since the birth of AI many seem to think that it will take over their jobs, yet what many fail to realize is that it will not only enhance our work but take over mundane tasks so that we may innovate at a faster pace. AI will always need the input of a human and so we should look to embrace it where we can. Another great article John!
AI/ML Platform Engineering at TD Bank
1 年Another interesting thing is yet another discipline comes into play....prompt engineering. Reminds me of the old UI modelers and storyboarding functions back in the 90s, but focus is more on optimizing prompts to leverage language models. I have created some simple qna chatbots and can get complex when need to interface with other services like layering knowledge mining capabilities (similar in layering openai on top of cogsearch for more semantic rich queries..). Interesting article on use cases beyond the typical conversational ones... https://www.dhirubhai.net/feed/update/urn:li:activity:7023697589967458304?updateEntityUrn=urn%3Ali%3Afs_feedUpdate%3A%28V2%2Curn%3Ali%3Aactivity%3A7023697589967458304%29
Advisor | Leadership | Analytics, AI/ML, Data and Strategy
1 年Great article John. I like to add some further thoughts from my experiences i have seen over recent years. The key term often used is augmentation to drive the acceptance of this modern approach to problem solving. I see this as a fundamental measurable axiom for enable organisation acceptance and success for AI. There plenty of industry AI hype but very few tangible impact stories that could have been solved easier using standard, established, and often cheaper approaches. However, I see a bright future for augmenting contextual AI support models within customer experience applications through the application of contextualised expert based systems and language models. Overall i see the journey to system nirvana will have plenty of headwinds which need strong cross-functional leadership, with supporting tangible lighthouse projects and a robust education program to support the workforce through this new mode of working.