Engineering.com Interview with Dr. Michael Connell: How to Deploy AI Responsibly

engineering.com | Enthought

Engineering.com Interview with Dr. Michael Connell, Enthought Chief Operating Officer:
How to Deploy AI Responsibly

Enthought | Michael Connell, PhD
Engineering.com spoke with Enthought COO Michael Connell, PhD to discuss how engineers can balance privacy, safety and limitations to leverage the power of AI-powered tools responsibly.

Connell has an extensive background in engineering and education as well as in how to leverage AI and machine learning to solve complex scientific challenges. He also recently participated in The White House’s Office of Science and Technology Policy call for public input to inform the U.S. AI strategy.

In the article, Connell discusses:
  • AI’s profound impact and recent disruption
  • Concerns around (lack of) regulation around AI and large language models (LLMs)
  • Thoughts on how to integrate responsibility into the training and usage of LLMs and other AI-powered tools

Read the full interview in engineering.com here.

Additional resources about AI and ML in scientific research here.

Share this article:

Related Content

Leveraging AI for More Efficient Research in BioPharma

In the rapidly-evolving landscape of drug discovery and development, traditional approaches to R&D in biopharma are no longer sufficient. Artificial intelligence (AI) continues to be a...

Read More

Utilizing LLMs Today in Industrial Materials and Chemical R&D

Leveraging large language models (LLMs) in materials science and chemical R&D isn't just a speculative venture for some AI future. There are two primary use...

Read More

Top 10 AI Concepts Every Scientific R&D Leader Should Know

R&D leaders and scientists need a working understanding of key AI concepts so they can more effectively develop future-forward data strategies and lead the charge...

Read More

Why A Data Fabric is Essential for Modern R&D

Scattered and siloed data is one of the top challenges slowing down scientific discovery and innovation today. What every R&D organization needs is a data...

Read More

Jupyter AI Magics Are Not ✨Magic✨

It doesn’t take ✨magic✨ to integrate ChatGPT into your Jupyter workflow. Integrating ChatGPT into your Jupyter workflow doesn’t have to be magic. New tools are…

Read More

Top 5 Takeaways from the American Chemical Society (ACS) 2023 Fall Meeting: R&D Data, Generative AI and More

By Mike Heiber, Ph.D., Materials Informatics Manager Enthought, Materials Science Solutions The American Chemical Society (ACS) is a premier scientific organization with members all over…

Read More

Real Scientists Make Their Own Tools

There’s a long history of scientists who built new tools to enable their discoveries. Tycho Brahe built a quadrant that allowed him to observe the…

Read More

How IT Contributes to Successful Science

With the increasing importance of AI and machine learning in science and engineering, it is critical that the leadership of R&D and IT groups at...

Read More

From Data to Discovery: Exploring the Potential of Generative Models in Materials Informatics Solutions

Generative models can be used in many more areas than just language generation, with one particularly promising area: molecule generation for chemical product development.

Read More

7 Pro-Tips for Scientists: Using LLMs to Write Code

Scientists gain superpowers when they learn to program. Programming makes answering whole classes of questions easy and new classes of questions become possible to answer….

Read More