Complying with the EU AI Act (AIA) guidelines while developing and implementing AI systems will soon be mandatory within the EU. However, practitioners lack actionable instructions to operationalise ethics during AI systems development. A literature review of different ethical guidelines revealed inconsistencies in the principles addressed and the terminology used to describe them. Furthermore, requirements engineering (RE), which is identified to foster trustworthiness in the AI development process from the early stages was observed to be absent in a lot of frameworks that support the development of ethical and trustworthy AI. This incongruous phrasing combined with a lack of concrete development practices makes trustworthy AI development harder. To address this concern, we formulated a comparison table for the terminology used and the coverage of the ethical AI principles in major ethical AI guidelines. We then examined the applicability of ethical AI development frameworks for performing effective RE during the development of trustworthy AI systems. A tertiary review and meta-analysis of literature discussing ethical AI frameworks revealed their limitations when developing trustworthy AI. Based on our findings, we propose recommendations to address such limitations during the development of trustworthy AI.

Artificial intelligence has already created the beginning of an apocalypse of sorts. Starting from attending to customer queries and optimizing logistics to detecting fraud and conducting analysis, the ascendancy of technology in business is no joke. While the influence of artificial intelligence (AI) is already taking a questionable stand, ethical issues are emerging. In many ways, the debate over AI ethics and risk assessment is going beyond a conclusion. In the business landscape, organizations are leveraging artificial intelligence and relative technologies, like machine learning, data analytics, cloud computing and more, to create a safer workplace.

Only 20% of companies report having an ethical artificial intelligence framework in place and just 35% have plans to improve governance of AI systems and processes in 2021, according to PwC data. I believe every CIO needs a responsible AI plan before implementing the technology. Businesses shouldn't wait for this to be mandatory. It doesn't matter if the CIO is buying the technology or building it. AI as a technology is neutral -- it is not inherently ethical or unethical.

Artificial intelligence has already created the beginning of an apocalypse of sorts. Starting from attending to customer queries and optimizing logistics to detecting fraud and conducting analysis, the ascendancy of technology in business is no joke. While the influence of artificial intelligence (AI) is already taking a questionable stand, ethical issues are emerging. In many ways, the debate over AI ethics and risk assessment is going beyond a conclusion. In the business landscape, organizations are leveraging artificial intelligence and relative technologies, like machine learning, data analytics, cloud computing and more, to create a safer workplace.