There is a consensus regarding the huge transformative potential of AI in economics and society, as it enables computer applications to perform tasks that typically require human intelligence, thereby enhancing efficiency. Though as expected there are controversy and numerous arguments surrounding the risks of Artificial Intelligence and associated areas like Generative AI, Deep Learning, etc.
The popularity and advancement of AI comes from huge progress in concepts like machine learning, deep learning algorithms, coupled with the availability of increased computing power and abundant data sources, which accelerated the development and accuracy of the AI. This has led to significant advancements in AI capabilities with various real-world applications across industries including pattern detection, speech recognition, recommendation engines, image recognition and decision-making systems.
While most industries are investing in Artificial Intelligence, there are pockets that are lagging due to various reasons like data privacy, usage of un-profiled data etc. Nevertheless, it is likely that AI technology will have a broad impact on value chain.
The intention of this article is to support the practitioners to move forward in a safe and trusted manner. These guidelines are adopted by government, quasi-government, and even private/public organizations. The Federal government has also issued an executive order on the safe, secure, and trustworthy development and use of AI. The order is more of an approach to ensure responsible innovation, development, and usage of AI across the broader economy.
Again, these are not any law, or policies, these are just guidelines that aim to set standards for AI, emphasizing safety, security, privacy protection, equity, consumer protection and workforce support.
Best Practices
The following key principles guide the organization for responsible and trustworthy AI development and usage.
1. Giving priority to safety, security, and transparency in AI systems, which involves understanding and mitigating risks effectively.
2. Encourage responsible innovation, competition, and collaboration in AI through investments in AI education, while ensuring fair and open marketplaces.
3. Ensuring support of all the human resources across the organization by providing training and education on AI advancements, while ensuring fair and open marketplaces.
4. Ensuring that AI policies promote equity and civil rights, preventing discrimination and bias in AI systems.
5. Protecting consumer interest by enforcing existing consumer protection laws and principles in critical fields where AI may pose risks
6. Safeguarding privacy and civil liberties by implementing measures to secure data collection and use, including the adoption of privacy-enhancing technologies and measures.
7. Managing risks associated with usage of AI within the realm organization’s own use as well as associated agencies.
8. Leading the efforts to develop and contribute towards a global framework for responsible AI usage.
There has been a lot of focus on ‘governance’ programs, that focus on development on AI Governance framework, and alignment with current governance frameworks. These help the company progress in a more balanced way. It’s critical that the leaders understand the risky aspects of these new technologies.
About the Author
Sid Priyadarshi is an accomplished digital transformation leader with extensive experience in agile project management, specializing in AI and data domains. With over 20 years of expertise, he excels in driving large-scale delivery programs and global business solutions.
His role as a catalyst for change is evident in his ability to conceptualize and implement cutting-edge technologies like Machine Learning and Artificial Intelligence, supported by a strong foundation in applied statistics. He currently is the Principal Consultant for AHEAD, an IT services and IT consulting company in Chicago, IL.
