Table of Contents
Question
What are the top moral and executive skill sets required when working with generative AI?
A. A rich technical background, especially in machine learning and natural language processing, coupled with excellent leadership skills.
B. Lobbying and diplomacy. Currently AI has a lot of unregulated parts so it is important to talk both sides of your mouth to not offend anyone involved in your team and other stakeholders.
C. Transparency, fairness, empathy and responsibility. Approach the production and all operations with caution, always ask “who is benefiting” from our generative AI solution.
Answer
C. Transparency, fairness, empathy and responsibility. Approach the production and all operations with caution, always ask “who is benefiting” from our generative AI solution.
Explanation 10
This is a skill set topic that requires some generative AI and ethical knowledge. Based on the information I found from various sources, I would suggest that the most accurate answer to your question is C. Transparency, fairness, empathy and responsibility. Approach the production and all operations with caution, always ask “who is benefiting” from our generative AI solution.
Generative AI is a type of artificial intelligence that can create new and original content, such as text, images, music, or code, based on user prompts or data inputs. Generative AI has many potential benefits and applications across various industries, such as art, writing, software development, product design, healthcare, finance, gaming, marketing, and fashion.
However, generative AI also poses some challenges and risks, such as ethical issues, legal issues, social issues, and technical issues. Some of these are:
- Ethical issues: Generative AI can create fake or misleading content that can be used to deceive or manipulate people, such as fake news or deepfakes. It can also raise questions about the ownership and authorship of the generated content, as well as the moral responsibility and accountability of the creators and users of generative AI.
- Legal issues: Generative AI can create content that infringes on the intellectual property rights or privacy rights of others. It can also create content that violates the laws or regulations of different jurisdictions or domains. It can also create content that is harmful or offensive to certain groups or individuals.
- Social issues: Generative AI can create content that affects the social norms or values of different cultures or communities. It can also create content that influences the public opinion or behavior of people. It can also create content that reduces the trust or credibility of human-generated content.
- Technical issues: Generative AI can create content that is inaccurate or biased due to the limitations or flaws of the data or algorithms. It can also create content that is difficult to verify or validate due to the lack of transparency or explainability of the generative AI models. It can also create content that is vulnerable to attacks or misuse by malicious actors.
Therefore, individuals working with generative AI must possess a strong moral and executive skill set to address these challenges and risks. Some of these skill sets are:
- Transparency: Individuals working with generative AI must be transparent about the sources, methods, and limitations of their generative AI models and outputs. They must disclose when and how they use generative AI to create content, and provide evidence or references to support their claims. They must also acknowledge any errors or uncertainties in their generative AI outputs and correct them promptly.
- Fairness: Individuals working with generative AI must be fair and respectful to all stakeholders involved in their generative AI projects, such as users, customers, partners, competitors, regulators, etc. They must ensure that their generative AI models and outputs do not discriminate against or harm any groups or individuals based on their characteristics, such as race, gender, age, religion, etc. They must also ensure that their generative AI models and outputs do not favor or disadvantage any groups or individuals based on their interests, preferences, opinions, etc.
- Empathy: Individuals working with generative AI must be empathetic and compassionate to the needs and expectations of their users and customers. They must understand the context and purpose of their generative AI outputs and how they affect the emotions and feelings of their users and customers. They must also consider the potential impact of their generative AI outputs on the society and environment at large.
- Responsibility: Individuals working with generative AI must be responsible and accountable for their actions and decisions involving their generative AI models and outputs. They must follow the ethical principles and guidelines established by their organizations or industries for using generative AI. They must also monitor and evaluate the performance and outcomes of their generative AI models and outputs regularly and take corrective actions when necessary.
In addition to these moral and executive skill sets, individuals working with generative AI must also approach the production and all operations with caution, always asking “who is benefiting” from our generative AI solution. This question can help them identify the potential beneficiaries and beneficiaries of their generative AI outputs, as well as the potential risks and harms they may cause. This question can also help them balance the trade-offs between different stakeholders’ interests and values.
Reference
- Microsoft’s First Generative AI Certificate Is Available for Free (techrepublic.com)
- Microsoft Launches Free AI Training Courses With Certification (techworm.net)
- AI Skills Initiative – Training and Resources | Microsoft CSR
- Microsoft is already offering a generative AI certification program | Engadget
- What every CEO should know about generative AI | McKinsey
- What Young Professionals Need to Know About Generative AI (hbr.org)
- The CEO’s Guide to the Generative AI Revolution | BCG
- An Executive’s guide to generative AI – KPMG United Kingdom
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