Cybersecurity and Data Protection
Description
The company only collects the minimal data required for its legitimate commercial purposes and is committed to the protection of employee, customer, supplier, and other data. Through policies, procedures, culture, and decision-making, the company and its representatives ensure the prevention of data misuse or unauthorised use. The company respects data sovereignty and maintains and follows clear policies regarding data ownership and data use authorisation, particularly for data about the company’s social and environmental context. The company has robust and safe Records and Data Management systems and practices. The company actively considers the ethical implications of machine learning, when relevant.
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Resources
Ethics guidelines for trustworthy AI
The High-Level Expert Group on AI has created ethics guidelines to promote trusworthy artificial intelligence (AI). According to the guidelines, trustworthy AI should be lawful, respecting all applicable laws and regulations; ethical, respecting all ethical principles and values; and robust, from both a technical and social environmental perspective. This guidance introduces seven key requirements that AI systems should meet in order to be deemed trustworthy and highlights assessment criteria to verify these requirements are being met. This is an importance resource for senior leaders, technology experts, and sustainability change agents of any large organisation that is considering developing and/or implementing AI into their operations. The High-Level Expert Group on AI was set up by the European Commission, the principles and recommendations of their guidance are applicable to every business regardless of industry or geography.
AI & The Future of Work: What Every MBA Needs to Know
This primer provides a helpful high-level summary of artificial intelligence that will benefit executives, board members, and other business leaders. It explains the concept and types of AI, as well as their impact on workers; highlights the risks of data bias and insecurity, privacy concerns, and regulatory risks; and examines the opportunities, such as those related to workforce training and collaborative machine-human applications.