Machine Learning Times
Machine Learning Times
EXCLUSIVE HIGHLIGHTS
The Quant’s Dilemma: Subjectivity In Predictive AI’s Value
 Originally published in Forbes, September 30, 2024 This is the...
To Deploy Predictive AI, You Must Navigate These Tradeoffs
 Originally published in Forbes, August 27, 2024 This is the...
Data Analytics in Higher Education
 Universities confront many of the same marketing challenges as...
How Generative AI Helps Predictive AI
 Originally published in Forbes, August 21, 2024 This is the...
SHARE THIS:

2 years ago
Early Thoughts on Regulating Generative AI Like ChatGPT

 
Originally published in Brookings, Feb 21, 2023.

With OpenAI’s ChatGPT now a constant presence both on social media and in the news, generative artificial intelligence (AI) models have taken hold of the public’s imagination. Policymakers have taken note too, with statements from Members addressing risks and AI-generated text read on the floor of the House of Representatives. While they are still emerging technologies, generative AI models have been around long enough to consider what we know now, and what regulatory interventions might best tackle both legitimate commercial use and malicious use.

WHAT ARE GENERATIVE AI MODELS?

ChatGPT is just one of a new generation of generative models—its fame is a result of how accessible it is to the public, not necessarily its extraordinary function. Other examples include text generation models like DeepMind’s Sparrow and the collaborative open-science model Bloom; image generation models such as StabilityAI’s Stable Diffusion and OpenAI’s DALL-E 2; as well as audio-generating models like Microsoft’s VALL-E and Google’s MusicLM.

While any algorithm can generate output, generative AI systems are typically thought of as those which focus on aesthetically pleasing imagery, compelling text, or coherent audio outputs. These are different goals than more traditional AI systems, which often try to estimate a specific number or choose between a set of options.  More traditional AI systems might identify which advertisement would lead to the highest chance that an individual will click on it. Generative AI is different—it is instead doing its best to match aesthetic patterns in its underlying data to create convincing content.

To continue reading this article, click here.

4 thoughts on “Early Thoughts on Regulating Generative AI Like ChatGPT

  1. Engler emphasized the increased attention AI models are receiving from policymakers due to their potential risks and benefits. The paper suggests the need for regulatory interventions to address both legitimate commercial uses and potentially malicious applications. However, the article does not go into specific regulatory proposals, leaving it an open question for further exploration. You can go to ChatGPT Online to search for specific proposals.

     
  2. Step into the shoes of a pizza chef and manager in papa’s pizzeria game. Take orders, prepare delicious pizzas, and serve customers in this engaging time management game. Handle every aspect of the pizzeria, from dough kneading to baking, ensuring each customer leaves satisfied.

     

Leave a Reply