IBM has announced the availability of three containerized Watson libraries, expanding their...
Recently, ChatGPT, a product of OpenAI, has received a great deal of attention from people all over the globe. This is a major achievement for the field of generative artificial intelligence (AI) developments and the underlying technology that supports many applications. This marks the end of a successful year for the industry.
IBM is currently at a pivotal moment for artificial intelligence (AI). More and more businesses are implementing AI and its developments, and advances in foundational research and development are making it possible for AI applications like generative AI to become even more advanced and effective. The possibilities for AI are vast, as it can help you analyze large amounts of data to find new solutions to various business and societal issues, such as sustainability, life sciences, customer service, employee experience, and more.
While these advancements are exciting, they also raise important questions within the industry. For example, how can we ensure that these models are being used responsibly and that their algorithms and outputs can be trusted? Generative AI models, in particular, can produce responses that are highly convincing and well-structured, making it difficult to identify incorrect responses without specialized knowledge of the relevant subject matter.
IBM is constantly engaging with clients and partners on these issues. The rapid pace of AI technological advancements means that businesses have a chance to put internal safeguards in place to govern the development and deployment of AI. At the same time, governments around the world are evaluating and implementing new AI regulations and guidelines.
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To increase the adoption of responsible AI developments, it is necessary to have a system in place to establish policies and accountability throughout the entire lifecycle of the AI. This system, known as AI governance, helps ensure that the AI follows principles such as fairness, transparency, robustness, and privacy. A successful AI governance strategy involves the coordination of people, processes, and technology.
AI governance processes within an organization help to determine the appropriate times, places, and methods for using AI within the business and to create policies based on the company’s values, ethical guidelines, regulations, and laws. At IBM, there is an AI Ethics Board that assists with centralizing the governance, review, and decision-making process for IBM’s ethics policies, practices, communications, research, products, and services.
AI governance technology can assist with implementing safeguards at each stage of the AI/ML lifecycle, including data collection, instrumenting processes, and transparent reporting to make needed information available to stakeholders. IBM recently introduced AI Governance, a solution that helps businesses gain a deeper understanding of what is happening within their AI systems. This solution is designed to help companies establish a consistent and transparent model management process, including capturing model development time, metadata, post-deployment model monitoring, and custom workflows. IBM has also created and open-sourced a set of Trusted AI toolkits, such as
AI Fairness 360,
Adversarial Robustness 360,
AI Explainability 360,
Uncertainty Quantification 360, and
AI FactSheets 360.
In addition to discussions on the importance of AI governance, advancements in the industry support IBM’s emphasis on meeting the specific needs of AI for business. Our clients want AI that is designed and managed by their subject matter experts and can be easily customized according to their business priorities and domain; AI that is reliable and accurate; AI that is able to handle and process complex, siloed data; and AI that follows principles of trust and transparency. These priorities guide the development of our AI software, such as IBM Watson Assistant and IBM Watson Discovery.
2022 has seen a continuation of the growing adoption of AI across various industries, as well as promising new developments in the field. We believe that businesses that implement AI governance early on will be better equipped to responsibly utilize this technology both now and in the future.
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