Dr. Anthony Rhem to speak at PrivSec & GRC Connect Chicago

Taking place April 16 and 17 at Crowne Plaza Chicago West Loop, PrivSec & GRC Connect Chicago provides a platform for organizations to address the cumulative nature of risk.

PrivSec & GRC Connect Chicago’s comprehensive agenda is led by subject matter experts, business chiefs and industry leaders, giving attendees a deep-dive into challenges and solutions on the rapidly evolving GRC landscape.

Event speaker, Dr. Anthony Rhem is CEO at A J Rhem & Associates Inc. He is a recognized thought leader, author and consultant in Artificial Intelligence, Knowledge Management, Big Data, Information Architecture, and Innovation.

Dr. Anthony Rhem will be attending PrivSec & GRC Connect Chicago to debate the ethical pitfalls of implementing AI systems.

You can learn more about Dr. Anthony Rhem and his discussion topic, below:

Could you briefly outline your career so far?

I started my career in Information Technology in 1982 after graduating from Purdue University. In the early years of my career in IT, I went from computer operator to programmer, programmer/analyst, to software designer/analyst.

After receiving my MS Degree from DePaul University in Computer Science/AI in 1989, I launched my consulting firm A.J. Rhem & Associates, Inc. During the 1990s, I partnered and worked with a few Expert System/Neural Network vendors on several projects with large organizations in the telecommunications, logistics, and manufacturing industries. 

In 1999, I was introduced to Knowledge Management and shifted my and my firm’s focus on Knowledge Management until 2015 when the advancements in big data technology brought me back to AI (specifically machine learning). I added this to my firm’s practice areas at the time, where now it’s a core service (along with Knowledge Management) that we provide. 

Along my journey, I have written several books and peer-reviewed articles on Knowledge Management, Artificial Intelligence and Information Architecture. I have also continued to upskill to keep ahead of what’s happening in business and technology by taking certification and degreed programs in Artificial Intelligence and Knowledge Management from Massachusetts Institute of Technology (MIT): AI Leadership; Walden University: Knowledge Management; Dartmouth University Tuck School of Business: Advance Executive Management Training, and Clark Atlanta University: Executive Management Training.

I also have the privilege of: serving as a member of the Board of Directors of System Integrators Inc. (1996-2000), founding Editorial Board Member of the AI & Ethics Journal (2020 – present); participating on the Corporate Advisory Board of Halen Technologies (2022-Present); the Technology Council of Advisors at Gerson Lehrman Group (GLG) (2010 – Present), where I provide insights on AI and Knowledge Management; National Science Foundation SBIR (Small Business Innovative Research) Review Panel in the areas of AI, Blockchain, IoT, Knowledge Management, and Education Solutions (2004-2017), and The Coach Lee Rose Foundation (2022-Present).

What are the main areas / themes that AI developers need to address in order to enhancing trust in AI?

I strongly believe that the main areas/themes AI developers need to address in order to enhance trust in AI are as follows: AI Ethics and Governance, Data Ethics, Critical Thinking, Fairness, and Bias Mitigation (understanding the data used to train AI models/algorithms), Privacy and Data Protection (ensuring the secure handling of data, implementing strong data encryption, anonymization techniques), Security and Safety (developing robust security protocols and regularly updating systems to defend against new threats), and Reliability and Performance (ensuring that AI systems are reliable and perform as expected).

What strategies can organisations using AI implement to help nurture trustworthy practices and systems?

Strategies include:

• Develop and enforce clear ethical guidelines and principles for AI development and use within the organization.
• Cultivate an organizational culture that emphasizes ethical responsibility among AI developers and users.
• Adopt technologies and methodologies that increase the transparency and explainability of AI systems.
• Regularly audit AI systems for biases and fairness issues.
• Implement robust data protection measures and privacy-preserving technologies.
• Promote and support a continuous monitoring of the performance of AI solutions to ensure systems remain effective, fair, and aligned with ethical guidelines.
• Educate and train employees by providing ongoing education and training on ethical AI development, data protection, and the societal implications of AI.
• Empower employees to raise concerns and suggest improvements for AI systems.