The Rise of AI in Classrooms, Labs and Industry – Part 3

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In summary, the rise of A.I. is a complex and multifaceted topic that encompasses a wide range of technologies. As such, it has already had a significant impact on industry and everyday society through the use of knowledge-based systems and big data. However, the term "A.I." is often misunderstood and can lead to confusion, as it actually refers to predictability adaptation rather than true artificial intelligence. This discrepancy is highlighted by the fact that biologists have a higher standard for sentience than computer scientists do. Additionally, there are challenges in ensuring the reliability of complex software systems, as demonstrated by past incidents such as the East Coast phone service crash and nuclear shutdowns.
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Greg Bernhardt
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We asked our PF Advisors “How do you see the rise in A.I. affecting STEM in the lab, classroom, industry and or in everyday society?”. We got so many great responses we need to split them into parts, here are the first several. This is part 3. Read part 1 here and part 2 here. Enjoy!
 

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Andy Resnick
That’s an interesting question, not just because the term ‘A.I.’ includes a whole range of technologies. There has already been significant and most likely permanent changes in industry and everyday society due to ‘knowledge based systems’ and ‘big data...

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The marketing term "A.I." is a misnomer that confuses people. What most people call AI is predictability adaption, basing actions on previous results. Like a servo controller with soft feedback.
Odd that biologists set such a high bar for sentience and computer geeks set the bar so low.
My father was an eminent Reliability Engineer. He could not understand Software Reliability since programs are logical mathematical constructs that either work or not. However enterprise software with millions of lines of code may be difficult to trace all possible failure modes and interactions in a finite period of time. The TelCo crash of east coast phone service and some nuke shutdowns as examples.
 

1. What impact will AI have on traditional classroom teaching methods?

AI has the potential to greatly enhance traditional classroom teaching methods by providing personalized learning experiences for students, automating administrative tasks for teachers, and analyzing student data to identify areas for improvement.

2. How is AI being used in scientific research labs?

In scientific research labs, AI is being used to analyze large amounts of data, identify patterns and trends, and make predictions. It is also being used to automate repetitive tasks and streamline experiments, allowing scientists to focus on more complex tasks.

3. Will AI replace human scientists in the future?

While AI may be able to perform certain tasks more efficiently than humans, it is unlikely to completely replace human scientists. AI is best used as a tool to assist scientists in their work, rather than as a replacement for their expertise and creativity.

4. How can AI be used in industry?

AI has a wide range of applications in industry, including streamlining manufacturing processes, optimizing supply chain management, and improving customer service through chatbots and virtual assistants. It can also be used for data analysis and prediction, helping businesses make more informed decisions.

5. What are the ethical concerns surrounding the use of AI in classrooms, labs, and industry?

Some of the ethical concerns surrounding AI include potential bias in algorithms, privacy concerns with the collection and use of personal data, and the potential for job displacement as AI automates tasks traditionally performed by humans. It is important for developers and users of AI to consider these concerns and ensure responsible and ethical use of the technology.

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