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

R&D Innovation in 2025

As we step into 2025, R&D organizations are bracing for another year of rapid-pace, transformative shifts.

Read More

Revolutionizing Materials R&D with “AI Supermodels”

Learn how AI Supermodels are allowing for faster, more accurate predictions with far fewer data points.

Read More

What to Look for in a Technology Partner for R&D

In today’s competitive R&D landscape, selecting the right technology partner is one of the most critical decisions your organization can make.

Read More

Digital Transformation vs. Digital Enhancement: A Starting Decision Framework for Technology Initiatives in R&D

Leveraging advanced technology like generative AI through digital transformation (not digital enhancement) is how to get the biggest returns in scientific R&D.

Read More

Digital Transformation in Practice

There is much more to digital transformation than technology, and a holistic strategy is crucial for the journey.

Read More

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