Checkin’ In On A.I. – What’s Been Changing

Checkin’ In On A.I. – What’s Been Changing

By Eli Amdur

It’s been nearly two years since I sounded the alarm and declared – without a shred of doubt – that A.I. will be the biggest transformation in human history. Considering things like stone tools, controlled use of fire, the wheel, clothing, agriculture, alphabets, printing, electricity, flight, TV, computers, space, and the internet, that’s a big statement – and I got roundly called out on it, mostly by conservative thinkers and Luddites. Please note, the use of the word ‘conservative’ carries no political overtones; it merely describes those who are reluctant to recognize anything that doesn’t fit their paradigms.

I went on to say that the nature, pace, and scope of change brought on by A.I. would be difficult to grasp at first but that we’d get it pretty soon.

I think, for the most part, we’re there, at least in theory. I certainly hope so, because as an independent career coach and advisor to corporate leaders, I had better be right.

Now here we are, two years later, and we no longer need to talk about A.I. in theoretical terms. A.I. has a history – and with all that’s happened in A.I. in two years, I think Bertrand Russell’s advice – “In all affairs it’s a healthy thing now and then to hang a question mark on the things you have long taken for granted.” – is sage.

How has A.I. changed?

So I decided it’s time once again to summon my respected brain trust – six thinkers with big minds and bigger imaginations – and I asked them one question: How has A.I. changed in two years?

This ought to show us how fast things are moving.

A.I. Ethics and Bias Mitigation

As A.I. made its splash, this was one of the first big areas of concern. It’s only gotten bigger. Algorithm development specifically for ethics and data bias has become a front-and-center issue. Researchers and practitioners are working closely here.

A.I. for Social Good

In our world of stubbornly persistent unresolved social issues – poverty, lack of access to clean water, healthcare disparities, illiteracy, environmental justice, humanitarian crises – we no longer have the means to solve them all unless, of course, we ramp up A.I.

Constant Advances in Deep Learning

Deep learning techniques in areas like computer vision, natural language processing, and reinforcement learning, have surged. Modeling is larger and more capable, enabling high performance of those who master it.

Transformer Architecture Dominance

Transformer-based models, with architectures like BERT and GPT, have become even more dominant in NLP tasks.

Progress in Reinforcement Learning

Researchers have been making great strides in areas like sample efficiency, transfer learning, and robustness. RL algorithms are being applied to real-world problems such as robotics.

Advancements in A.I. Hardware

As A.I. grows exponentially, the hardware=re it runs on will have to, also. Developments such as GPUs, TPUs, and neuromorphic chips, to support the growing computational demands of A.I. algorithms are in play. This includes energy-efficient hardware.

AI Governance

By nature, cautious regulation and warp-speed technology progress are in combat with one another.

Governments and regulatory agencies are establishing guidelines for responsible use of A.I. in areas

like privacy, accountability, and societal impact.

AI and Cybersecurity

A.I. is increasingly critical in cybersecurity, threat detection, and fighting malware. Defending against A.I. attacks is also an active area of research.

One more thing…

My gurus urged me to tell you that between the time this report posts and the time you read it … it will already need an update.