Top 6 AI Model Quality Trends to Watch Out for in 2023

The top 6 AI model quality trends to watch out for in 2023 are essentially enlisted in this article

We can expect to see a continued spotlight on these top 6 AI model quality trends in 2023 and help companies achieve a return on their growing AI investments. anticipate more public relations disasters that could have been avoided with improved AI model quality trends

The top 6 AI model quality trends in 2023:

A Movement Towards More Formal Testing and Monitoring Programs for AI models: Similarly, to software development 20 years ago, business software use did not take off until testing and tracking became commonplace. Intelligence is approaching a comparable tipping point. Machine learning and artificial intelligence technologies are rapidly being accepted, but their quality differs. Often, the data scientists who create the tools are also the ones who physically evaluate them, which can result in blind spots. Manual testing is time-consuming. Surveillance is new and haphazard. And the quality of AI models is extremely variable, becoming a deciding element in the effective adoption of AI. Automated testing and tracking ensure quality while reducing ambiguity and risk.

AI Model Explainability stays Hot: As AI becomes more prevalent in people's daily lives, too many people want to understand how the algorithms function. Internal partners who need to believe the models they are using, consumers who are affected by model choices, and authorities who want to ensure that consumers are handled equitably are driving this. 

More Debate about AI and Bias. Is AI a Friend or Foe of Fairness: People were concerned in 2021 and 2022 that AI was creating bias due to variables such as poor training data. In 2023, I believe there will be an increasing awareness that AI can eliminate prejudice by avoiding the historical moments where bias was present. People are frequently more biased than computers; we are beginning to see methods for AI to minimize bias rather than add it.

More Zillow-like Debacles: Until testing and tracking become common practice, businesses will continue to battle with quality problems such as the ones Zillow encountered in its home-buying section (Old versions cause the business to overbuy at exorbitant rates, eventually leading to the division's closing and huge losses and unemployment). In 2023, I anticipate more public relations disasters that could have been avoided with improved AI model quality methods.

A New Vulnerability in the Data Science Ranks: There has been a serious dearth of data scientists for several years, and businesses that have them have treated them like treasures. However, as the difficulty of showing ROI on AI efforts continues, and as the economy softens, businesses are adopting a tougher stance on outcomes. Only one out of every ten models created currently is used in production. Data science teams that are unable to rapidly deploy models into production will experience increased strain. Those positions may not be safe indefinitely.

Formal Regulation of AI uses in the U.S.: Unlike the European Commission, US governing agencies have been studying the challenges and effects of AI but have yet to make a major move. That will change in 2023 when the United States will eventually write its federal regulations, similar to those already in place in the EU and Asia. Guardrails benefit everyone in this market and will eventually help create confidence in AI. Regulations in the United States are not far away, and companies should prepare. The latest White House Blueprint for an AI Bill of Rights, which was published in October 2022, is a move in the correct direction, offering a foundation for responsible AI creation and use.