Five Industry Experts Address Risks in a Gold Age of Artificial Intelligence and Machine Learning
An article by David Churbuck, former editor-in-chief of Forbes magazine
In August 2022, Wow AI, a global provider of high-quality AI training data, invited a panel of experts to discuss the role of data in AI, why it has been in the limelight in recent years, as well as the risks and ethics of AI.
The five experts are:
- David Von Dollen, former head of AI at Volkswagen North America
- Patrick Bangert, VP of Artificial Intelligence at Samsung SDS American
- Noelle Silver, founder of the AI Leadership Institute, and Global Partner, AI & Analytics at IBM
- Andreas Welsch, VP & Head of Market & Solution Management — Artificial Intelligence, SAP
- Aravind Ganapathiraju, VP of Applied AI at Uniphore
The first topic they discussed was the risks of an AI going out of control and how to improve users’ trust in AI ethics. Noelle Silver, who was involved in the process of introducing Amazon Alexa to the market and making AI-powered applications more widely known, believed that smartphone apps are more threatening to our privacy than Alexa. She stated:
“I’ve consistently been opposed to AI being applied to anything demographically oriented. […] Biases end up perpetuating bad behavior. Maybe the models need to be infused with some inclusivity.”
David Von Dollen had the same idea, saying that applications using narrow AI — an algorithm that’s trained on a specific set of data to perform a specific task may turn out to be harmful, much more so than some sentient AI taking over in a Skynet situation.
Andreas Welsch thought making sure that the people who are affected by the change are part of the process would build the strongest bond and trust when the new systems occur.
Then, explaining why AI has been in the spotlight after years of being ignored, the former head of AI at Volkswagen, David von Dollen affirmed that computing power in the form of GPUs and algorithm refinements have been the two biggest contributors.
Aravind Ganapathiraju, VP of Applied AI at Uniphore & Patrick Bangert, VP of AI at Samsung SDS agreed and added that the systematic accuracy, speed, and novel modeling methods have made all the difference.
Finally, the role of data in building and scaling AI was touched upon. Since an extensive amount of data is required to develop any AI/ML system, concerns over personal data privacy arise. Aside from strict rules and regulations preventing privacy violations, what should providers of AI-enabled products and services consider when it comes to data?
Aravind Ganapathiraju shared a program Uniphore had recently introduced called “Q for sales”, which analyzes conversations by examining the tonal information in a call, facial expressions, and other visual cues. The company declared that the fusion of different data types — going from audio to text, from video to facial expressions — provides valuable insights to gain a better outcome and shall mark future approaches to data collection.
Andreas Welsch said that due to a data influx and the availability of many data pools, it’s not possible for one individual human being or a team of data scientists to analyze everything by themselves. With the help of AI, businesses are able to detect patterns in the data which allows them to automate certain parts of their business processes in a way that has never been possible before at such a level of scale.
For a global corporate like Samsung that trains all sorts of models, data plays an even bigger role, said Patrick Bangert:
“The role data plays across the company in driving AI systems to forecast how many people will buy a particular Samsung device, at which stores, and how to get inventory to those stores upon launch. […] Our internal data is the fuel for those forecasting systems and unique to our business and our success.”
Noelle Silver claimed that Web3 was forcing people to rethink data and go from giving up their data in exchange for free emails or photo storage to saying “You can use my data, you can even make money off my data, but there needs to be equity in understanding how the data is being used.”
Therefore, companies should become more responsible and ethical stewards of their users’ data.
They will share more insights along with more than 20 other AI/ML thought leaders recruited from the Fortune 500 and worldwide organizations such as Walt Disney, Deloitte, Microsoft, Oxford Brookes University, The US Department of Commerce, and many others, during the Worldwide AI Webinar, a two-day online discussion of contemporary AI and ML trends on September 29–30 hosted by Wow AI.
*This article was re-edited from the original post written by David Churbuck, the founder and former editor of Forbes and a prize-winning tech journalist. It was picked up by over 500 publications and online newspapers including Cision PR NewsWire, AI Tech Park, and MarketWatch.
Read the original article here.
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