By Naveen Rao, Vice President and General Manager, Artificial Intelligence Products Group
The computational advances of the past few years have enabled a new era of innovation – one in which machines can analyze vast amounts of data and find useful insights in that data. This is Artificial Intelligence (AI). With the proliferation of large data sets, computers can now solve problems that previously required human intervention.
As with previous revolutions in industrial development, the possibilities for applying AI to improve societies and advance human welfare are substantial. Intel is working across industry,government, and civil society to make these advancements in consideration of the global technological, economic, social, and cultural contexts in which they will be leveraged. One of these contexts is a public policy environment that considers the tremendous complexity behind implementing technology that makes decisions based on human-defined datasets. As important as where AI will get used is how AI will get used; a public policy conversation is necessary now as we work to develop new methods for integrating AI capabilities into the fabric of society.
Today, we’re proud to release Intel’s first AI Public Policy white paper that offers a set of public policy principles to further discussions and debate among technologists, academics, data scientists, policymakers, and the public. It is our vision that policymakers around the world can integrate these principles into workable policy frameworks.
- Foster Innovation and Open Development – To better understand just how impactful AI can be in our lives and continue to explore the spectrum of applications, policy should encourage investment in R&D in AI sectors. Governments should support the controlled testing of artificially intelligent systems to help industry, academia, and other stakeholders improve our systems.
- Create New Human Employment Opportunities and Protect People’s Welfare – AI will change the way many of us work. Public policy in support of adding skills to the workforce and promoting employment across sectors should enhance our workforce while also protecting people’s welfare.
- Liberate Data Responsibly – AI is powered by access to data. While maintaining security and data privacy, machine learning algorithms improve by absorbing more data over time; data acquisition is imperative to achieving more enhanced model development and training. Keeping data moving will help machine learning and deep learning reach its full potential.
- Rethink Privacy – Many privacy frameworks like The Fair Information Practice Principles and Privacy by Design have withstood the test of time and the evolution of new technology. But with major technological advancements, we have had to “rethink” how these models apply in the new environment.
- Require Accountability for Ethical Design and Implementation – The social implications of computing have grown and will continue to expand as more people have access to smart systems. Policies should work to identify and mitigate discrimination in algorithms and encourage diversity in design thinking.
Additionally, Intel is excited to announce the launch of a Blog Series dedicated to exploring the vast scope of AI implementations across different industries – from cybersecurity to agriculture and everything in between. As October is Cybersecurity Awareness Month in the United States, Europe and Australia, the first entry will feature an examination of AI’s implementations in cybersecurity to better predict and prevent cyberattacks and security breaches. Sign up to receive this and future posts at Intel’s policy blog site.
GM, Artificial Intelligence Products
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