Pulse Community Insights

What tech leaders really think about AI and ML ethics, benefits, and risks

Tech Trends & Future of Work

October 29, 2021
·
5
min read
AI and ML ethics

AI and ML ethics

Artificial intelligence (AI) and machine learning (ML) are some of the most common buzzwords that are mentioned in the Pulse community. Conversations on Pulse cover many facets of this technology, including AI and ML ethics and governance, benefits of using AI and ML technology, and perceived security risks that deter AI and ML adoption. Here’s a short summary of what technology leaders really think about using AI and ML.


AI and ML ethics and governance

Do you think government regulation will stifle the evolution of AI technology?

“In terms of the ethical side of AI, it's up to us to actually ensure that that occurs or we’ll see a repeat of what happened with the payment card industry [...] if we don't figure it out and self-regulate, Uncle Sam's going to come in and do it for us and it won’t be pretty and it won’t be flexible and it will stifle innovation despite their best intentions.”

–⁠ Director of Security Operations

AI and ML ethics: inequalities in technology
Elisha Herrmann, Senior Director of Digital Transformation at Navisite, conveys how gender biases are put forth in ML technology in one of our recent blog posts on women in IT leadership.


Benefits of using AI and ML technology

Where can you see AI technologies making the biggest impact at your organization?

“I think AI will provide tremendous value in terms of vulnerability management as we start looking at larger fluid enterprises—meaning cloud-based ones that are restocked on a regular basis and expanding and contracting constantly—that truly can derive value.”

–⁠ Director of Security Operations

📊 Featured report on artificial intelligence benefits
Read our One-Minute Insight Report on AI Strategy in 2021 to learn about how AI and ML technologies are used in real-world applications to provide valuable business insights, improve cybersecurity risk management, reduce operational costs, and more.


Has COVID accelerated the adoption of Artificial Intelligence (AI) and Machine Learning (ML)?

“COVID has just continued to accelerate the adoption of AI and machine learning. And the enterprise was already on track, but I think it's been exciting to see places in healthcare and finance become more data-enabled and data-driven. Bringing those legacy enterprises into a more digital-first world has actually been really exciting to me.”

–⁠ Venture Capital Investor


Potential security risks and concerns when using AI and ML

What are the biggest security pitfalls when it comes to AI?

“The security or risk aspects of AI are twofold. One is the risks associated with AI and the ethical, privacy, and security implications that could be negative. Then there's AI used in the context of security that has its own set of not only risks but also benefits. The potential dangers with AI in security lie in how it's used.”

–⁠ Malcolm Harkins, Chief Security and Trust Officer at Epiphany Systems


Have safety concerns or security risks stopped you from implementing AI technology?

“If it is properly implemented with proper principles and properly managed and maintained, then I'll take AI wherever I can get it. I don't have enough bodies, resources, or time to manage the multiple petabytes of data that come my way and I want to be able to refocus my teams to do it. But all of those caveats need to be in place. My challenge isn't where it can be useful, it’s that I want those principles in place and don’t see a lot of them right now.”

–⁠ Director of Security Operations


What are your biggest concerns as AI capabilities become a standard industry offering?

“...computers can never develop intuition, which relies on gut feelings; a deep emotional response. We can model other kinds of emotions and interactions, but intuition—often referred to as the "sixth sense"—cannot be programmed. Taking this out of the equation in decision making (or worse, attempting to create a mathematical model) is a path we should not attempt.”

–⁠ CTO


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