Gartner recently published a series of research reports on Predicts 2021, including one that highlights the serious, wide-reaching ethical and social problems that artificial intelligence (AI) predicts could create in the next few years.
Companies have been coerced into investing in artificial intelligence technology by the race for digital transformation and data abundance. Even the pandemic of COVID-19 is the ideal cause for that! And with that, in discussions between governments, companies, and other tech purists and critics, the idea of exploiting responsible AI took center stage.
A fast search pattern shows that in the past five years, terms such as “Ethical AI” and “Responsible AI” have gained prominence. But what is the reasoning behind it? Currently, the presence of bias and lack of accountability (black box) in training data for artificial intelligence models undermines the prospect of using AI for good. Although explainable AI and trustworthy AI promise to fill in the gaps, they are not enough on their own.
During the creation and implementation of artificial intelligence systems, this type of AI aims to recognize the ethical, moral, legal, cultural, and socio-economic implications. In short, it accommodates and encourages the pursuit of ethical, accountable, interpretable, qualitative, and transparent AI, something that was lacking in helpful AI and ethical AI!
Responsible AI can refer to the vast trove of factors like removing model bias, improving data safety, equal pay for members of the AI supply chain, and more. Although it is more than specifying technical discipline criteria, many have not understood why it could be irreversible and problematic to misuse artificial intelligence. As per a 2018 global executive survey on Responsible AI by Accenture, in association with SAS, Intel, and Forbes, 45 percent of executives believe that not enough is known about the unintended consequences of AI.
Therefore, the clarion call for responsible AI has increased in academia, industry, and government circles with a sharp rise in the use of artificial intelligence in business. Although such trade-offs need to be taken into account, government bodies may play a key role in pushing Responsible AI into the business framework.
A strong Responsible AI system focuses on mitigating AI risks with imperatives that address four main areas, with 2021 being touted as the year when Responsible AI will be a significant tech trend. There are the following: governance, design and execution, control and operation, and reskilling. Also, an ethical code must be established in addition to the administrative and legal process, which stresses data security and IP, privacy, openness in decision-making, and prevention of social dislocation.
Canada continues to be a pioneer at present and shares its responsible use of AI in its government operations. In December last year, AI Global convened its first meeting on the new Responsible AI Qualification Programme in collaboration with the World Economic Forum and the non-profit Schwartz Reisman Institute (RAIC). And the prime minister of India, Narendra Modi, stressed that the Transparency Algorithm is crucial to building confidence in the use of artificial intelligence and that it remains our collective duty to ensure it. Also, an ethical code must be established in addition to the administrative and legal process, which stresses data security and IP, privacy, openness in decision-making, and prevention of social dislocation.
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