Article Links Published by Neil Raden on Issues of AI and AI Ethics on Diginomica: 2022-August 2023

Neil Raden

3 min readSep 3, 2023

Generative AI in the enterprise - re-assessing the risk factors

Assessing generative AI risks may seem like catching a moving train from behind. New thinking about generative AI…

From grid optimization to data management - can AI revolutionize the energy industry?

The complexities of modern energy management combine grid management with the incorporation of renewable energ

Can AI solve the messy data predicament?

Messy data brings a dose of reality to analytics projects everywhere - it's a problem for AI projects as well. But can…

The disparate impact metric falls short for fairness in algorithmic models - here's why

As we attempt to build AI models that achieve fairness, approaches to protecting marginalized groups like differential…

What have we learned about AI ethics? It's time for risk-based regulations

The bad news? The typical approach to AI ethics hasn't worked. But a way forward is emerging - via a growing momentum…

Enterprise AI ambitions are at odds with distrust towards AI

All we hear about is the massive transformative potential of AI. But on the ground, the reality of AI perceptions is…

Generative AI needs better context - you can't talk about Large Language Models without reverse…

The hype over Large Language Models (LLMs) has reached a fever pitch. But how much of the hype is justified? We can't…

Assessing the value of synthetic data for AI - public policy issues take center stage

The online fervor over synthetic data exceeds its viability. But when it comes to public policy and data privacy, does…

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The insurance implications of AI are heating up — reviewing the NAIC’s Model Bulletin for the use…

The NAIC’s highly anticipated Model Bulletin for the use of algorithms, predicative models and AI came out in July, but…

Autonomous weapons systems - a cautionary use case for evaluating AI risks

Lethal autonomous weapons systems bring the ethical concerns of Artificial Intelligence to a head. The use of such…

NIST's AI risk management framework - is this a way forward for AI ethics, and trustworthy AI?

NIST's AI risk management framework (RMF10) is now official. So what's changed? A welcome and surprising approach to…

We're stuck in the AI ethics fishbowl - so how do we get out?

Live AI systems, already operating at scale, can have dangerous consequences - and concerning downsides. In theory, the…

Can AI help us address food insecurity and food waste?

Despite all our tech-for-good efforts, food insecurity remains a global problem. Meanwhile, the stats on food waste in…

It's time for AI ethics to get real

After five years of AI ethics, it's time to get real. We need better projects - and a better approach to the pitfalls…

AI needs foundational models - so what can we learn from GPT-3, BERT, and DALL-E 2?

Foundational models address a fundamental flaw in bespoke AI. But foundational and large language models have…

Stop blaming humans for bias in AI? Who else should we blame?

If humans aren't to blame for AI bias, who is? We can point to the data, but the data isn't static either. A recent…

"I can build this - but should I?" Welcome to the AI crime prediction debate

Can you predict crime with AI? And what should be done with these predictions, and the data that powers them? An AI…

Think AI can aid decision-making? Only if you address the risk of bias in the last mile

AI has the potential to aid decision-making at scale - but there are obstacles. One of the trickiest to unravel is…

Why are we failing at the ethics of AI? A critical review

Sometimes the AI ethics conversation appears to be a morass of well-meaning platitudes, without forward direction. A…

How does AI and model bias impact DEI in financial services and insurance? Answering the to…

What is the impact of DEI on the life insurance and financial services industry? Does AI bring new risks due to bias in…

Article Links Published by Neil Raden on Issues of AI and AI Ethics on Diginomica: 2022-August 2023

Generative AI in the enterprise - re-assessing the risk factors

Assessing generative AI risks may seem like catching a moving train from behind. New thinking about generative AI…

From grid optimization to data management - can AI revolutionize the energy industry?

The complexities of modern energy management combine grid management with the incorporation of renewable energ

Can AI solve the messy data predicament?

Messy data brings a dose of reality to analytics projects everywhere - it's a problem for AI projects as well. But can…

The disparate impact metric falls short for fairness in algorithmic models - here's why

As we attempt to build AI models that achieve fairness, approaches to protecting marginalized groups like differential…

What have we learned about AI ethics? It's time for risk-based regulations

The bad news? The typical approach to AI ethics hasn't worked. But a way forward is emerging - via a growing momentum…

Enterprise AI ambitions are at odds with distrust towards AI

All we hear about is the massive transformative potential of AI. But on the ground, the reality of AI perceptions is…

Generative AI needs better context - you can't talk about Large Language Models without reverse…

The hype over Large Language Models (LLMs) has reached a fever pitch. But how much of the hype is justified? We can't…

Assessing the value of synthetic data for AI - public policy issues take center stage

The online fervor over synthetic data exceeds its viability. But when it comes to public policy and data privacy, does…

The insurance implications of AI are heating up — reviewing the NAIC’s Model Bulletin for the use…

The NAIC’s highly anticipated Model Bulletin for the use of algorithms, predicative models and AI came out in July, but…

Autonomous weapons systems - a cautionary use case for evaluating AI risks

Lethal autonomous weapons systems bring the ethical concerns of Artificial Intelligence to a head. The use of such…

NIST's AI risk management framework - is this a way forward for AI ethics, and trustworthy AI?

NIST's AI risk management framework (RMF10) is now official. So what's changed? A welcome and surprising approach to…

We're stuck in the AI ethics fishbowl - so how do we get out?

Live AI systems, already operating at scale, can have dangerous consequences - and concerning downsides. In theory, the…

Can AI help us address food insecurity and food waste?

Despite all our tech-for-good efforts, food insecurity remains a global problem. Meanwhile, the stats on food waste in…

It's time for AI ethics to get real

After five years of AI ethics, it's time to get real. We need better projects - and a better approach to the pitfalls…

AI needs foundational models - so what can we learn from GPT-3, BERT, and DALL-E 2?

Foundational models address a fundamental flaw in bespoke AI. But foundational and large language models have…

Stop blaming humans for bias in AI? Who else should we blame?

If humans aren't to blame for AI bias, who is? We can point to the data, but the data isn't static either. A recent…

"I can build this - but should I?" Welcome to the AI crime prediction debate

Can you predict crime with AI? And what should be done with these predictions, and the data that powers them? An AI…

Think AI can aid decision-making? Only if you address the risk of bias in the last mile

AI has the potential to aid decision-making at scale - but there are obstacles. One of the trickiest to unravel is…

Why are we failing at the ethics of AI? A critical review

Sometimes the AI ethics conversation appears to be a morass of well-meaning platitudes, without forward direction. A…

How does AI and model bias impact DEI in financial services and insurance? Answering the to…

What is the impact of DEI on the life insurance and financial services industry? Does AI bring new risks due to bias in…

Written by Neil Raden