Organizations that employ artificial intelligence (AI) technology must act responsibly, especially when it comes to customer data. AI and the machine learning models that support it must be comprehensive, explainable, ethical and efficient. Responsible AI is an emerging area of AI governance and the use of the word responsible is a general term that encompasses both ethics and democratization. To ensure that companies create and implement AI responsibly and in compliance with regulations, there are several steps to take. The blockchain is a useful tool for recording every step of the development process in a human-readable format that cannot be modified.
Web 3.0 is still in development, but there are plenty of tools to develop next-generation web applications and close the gap with it. Organizations should also create a framework, usually documented on their website, which explains how they approach accountability and ensure that the use of AI is not discriminatory. The IBM AI Ethics Council is a central body that supports the creation of ethical and responsible AI across IBM. Kathy, the principal architect of the ethical AI practice at Salesforce, develops research-based best practices to educate Salesforce employees, customers, and the industry on the development of responsible AI. The search for responsible and ethical AI and technology is fundamental and goes beyond any company or organization.
An important goal of responsible AI is to reduce the risk that a minor change in the weight of an input will dramatically change the outcome of a machine learning model. FICO has created responsible AI management policies to help its employees and customers understand how the machine learning models used by the company work, as well as what are the limitations of programming. Just as ITIL provided a common framework for the delivery of IT services, advocates of responsible AI hope that a widely adopted framework for the governance of AI best practices will make it easier for organizations around the world to ensure that their AI programming is human-centered, interpretable and explicable. Resolving ambiguity about who is responsible if something goes wrong is an important factor for responsible AI initiatives. Continuous scrutiny is crucial to ensure that an organization is committed to providing unbiased and reliable AI. For this reason, some companies use the blockchain, the popular distributed ledger used for cryptocurrency bitcoin, to document the use of responsible AI.
