Technology itself is not “good” or “bad,” but how people use it has a positive impact. … [+]
Late last year, a panel of experts joined the authors at a debate held at Lloyd’s of London, and found out whether artificial intelligence (AI) will ultimately benefit or harm people, organizations and society. We debated whether it was a “utopia” or a “dystopia.” The event was conducted in collaboration with the World Innovation Network (TWIN Global) and was attended by over 30 leading AI experts from academia, banking, insurance, and technology. Our discussions found that effective leaders are making AI governance efforts that enhance the benefits of the technology and reduce its risks.
Utopia view – Panelists discussed some of the ways AI can benefit people, organizations, and society. The most common short-term benefit of AI is that it can improve the productivity of knowledge workers in their daily tasks. Workers become more productive and efficient, which improves work-life balance, physical health, career growth, employee income, and company financial health. For example, generative AI tools like ChatGPT and Bard allow employees to harness the power of “virtual colleagues” to add more value. As emerging generations become “AI natives,” machine learning tools will provide opportunities in ways previously unanticipated or understood. People have been afraid of most new technologies: airplanes, polio vaccines, PCs, spreadsheets, and even can openers. They felt that its use was disconnected from natural processes and was causing confusion. History has shown that technology, when understood and used constructively, can have great benefits.
Dystopia View – Panelists also articulated a number of risks of AI that can negatively impact people, organizations, and society, and are commonly associated with disruption. For example, there are concerns that AI will make workers more vulnerable to downsizing and layoffs. AI may also lead to the creation of new jobs, but these jobs may require skills that many workers currently do not have or are difficult to acquire. Additionally, AI could lead to increased wealth inequality as the gap between high-skilled and low-skilled workers widens. Additionally, there are risks of misinformation (such as influencing public opinion), data security breaches, and intellectual property misuse (as highlighted by recent lawsuits such as the New York Times case against Open AI). In extreme cases, humans could become “machine-hijacked” and lose control, allowing AI to act in destructive ways of its own volition.
Governance – Panelists explained how effective leaders are practicing good governance when it comes to AI and other emerging technologies. This includes the following actions:
· Understand how AI and other technologies work: When generative AI was introduced, many users mistakenly thought the tool was just an advanced search engine rather than a text or code generator. The tool caused “hallucinations” and other errors that could have been avoided. Effective leaders don’t just understand: the purpose As well as technological advances, they also learn how They engage and deepen their understanding what There are things they can do and things they can’t do.
· Educate users and other leaders: Good governance includes educating those responsible about the benefits of AI, risks, and how to use the tools responsibly. For example, effective leaders create high-quality prompts, coach users to verify the accuracy of content, and coach reviewers on what red flags to look for in processes and output. Masu.
· Establish ethical usage standards: Effective leaders encourage users’ ability to respect privacy and copyright, cite sources, and use information responsibly. For example, ethical use standards may include techniques that generate content from a set of known and verified documents rather than from a broader Internet-based learning model as a whole.
· Keep sensitive information safe: Effective leaders establish guidelines and procedures to ensure that sensitive data is not exposed to the public. This includes policies and processes to prevent sensitive information from being exposed through AI learning and training, and to ensure legal and security reviews of AI services.
· address bias: Effective leaders take steps to ensure objectivity and fairness of data inputs and outputs. They maintain standards for the data used to train AI models and how the output is reviewed to reduce the impact of analytical and social biases.
· Understand the rules and responsibilities:Effective leaders know that legal liability and its impact can be difficult to track. Country-specific and local regulations vary widely, and good governance requires understanding and action to prevent problems and quickly address them when they occur.
· think ahead:Effective leaders don’t wait for problems to surface before addressing them. For example, understanding the impact of AI on jobs, workers, and skill availability long before change occurs can give companies a competitive advantage and create constructive use scenarios for the technology. Masu. The same goes for data security issues, programming issues, and other potential pitfalls. The most effective organizations began implementing skills training and data protection measures as soon as the use of generative AI became widespread.
Panelists emphasized that technology itself is not “good” or “bad”; rather, it is the way people use it that leads to positive or negative outcomes. Effective leaders are proactively working to better understand and address the complexities of AI and other related technologies such as blockchain, metaverse, and quantum computing. They recognize that complete control is neither possible nor realistic, and they have a responsibility to provide good governance over what they can influence.
