D&O insurance: Impact and risks of artificial intelligence and its use by the board of directors in decision making
It may be tempting to think that tools such as ChatGPT, Bing, Bard and Perplexity AI speed up this process by finding information for you on a topic and answering your questions directly. However, it is important to know a little more about genrative ai how these tools work, the information they provide, and to think critically about whether the information they create is appropriate for your intended use. “If an AI model is trained using biased data it results in a biased outcome.
By leveraging generative AI, governments can create more efficient, sustainable, and liveable cities. Generative AI can create personalized, easy-to-understand communications at scale, to keep citizens informed about public sector initiatives and services. By making complex information more accessible, LLMs can foster increased public engagement and trust in government institutions. There is no limit to how Generative AI could transform existing industries or spark innovative new business models as the technology evolves. Whether released via API or open source, a single issue with a model at the foundation stage could create a cascading effect that causes problems for all subsequent downstream users.
Information Age: How to implement AI and advanced analytics, and observe the technologies’ transformational impact
By analyzing the context and relationships between words, the model learns to generate coherent and contextually appropriate responses. Trustees and management teams need to consider its potential, from creating new content to positively impacting productivity, innovation and ethics within an evolving regulatory environment. In doing so, generative AI can be one of the most transformative technologies of our time.
It’s this accessibility that may prove to be one of ChatGPT’s most impressive feats; never before has the public had access to AI tech with such far-reaching capabilities. In the long term, it is likely that these ethical challenges will become more complex as the technology continues to progress. As generative models become more sophisticated, the current concerns in relation to matters like privacy may be accentuated by the technological advances.
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Alternatively, certain academics have suggested a disclosure based regulatory approach, which seems similar to SEC regulations and disclosure obligations for US public companies. They suggest that such a framework would be most suitable because the cost would not unduly restrict innovation and investment in AI, yet the level of disclosure still provides the needed oversight in a developing industry. For example, Samsung banned use of ChatGPT after employees loaded sensitive company data onto genrative ai the platform that subsequently leaked.[xv] Further, legal and regulatory frameworks in the US do not currently recognize non-human directors. Therefore, significant questions regarding legal liability are likely to present where AI takes a greater role in corporate decision making. From personal experience, AI often speeds up basic processes, such as paying for goods or predictive text and searches. The lure of the same time saving benefits are also present in the corporate board room.
Organizations have been using predictive AI for some time now, but as Bonaci notes, ”What makes predictive AI even more powerful, is the ability to leverage real-time data to power in-the-moment experiences and recommendations for customers. Bonaci says, “Models that predict the future based on what’s happened in the past … helps businesses enable and anticipate customer behavior, forecast market demands, optimize operations, or any other type of data-driven decision. Major companies such as PepsiCo are already utilising AI to empower creators and enhance human connection, just not in the same ways as our test. Through pre-launch testing of ad and product concepts, AI interprets large volumes of real-time data from core consumer audiences.
Similar to other AI models, it is important for firms to have a robust AI framework and governance in place with Explainable & trustworthy AI frameworks. Challenges remain with leveraging the preexisting models which are already trained on publicly available data sets, as they could potentially contain false and misguided information leading to decision errors. The ability of Generative AI to create and innovate while saving cost and time is revolutionising many industries. By understanding and implementing these applications, business leaders can drive their organisation’s growth and competitiveness in an ever-evolving marketplace.
That’s why Choice Hotels International adopted an AI-based tool – Schneider Electric’s EcoStruxure Resource Advisor – to better monitor and proactively manage energy consumption at its 6,000 hotels. It’s early days for this effort, but the company says that with this tool, its hotel owners will be better able to understand and manage the energy usage in their commercial buildings. Generative AI tools not only produce written language and images, but also churn out computer code. Goldman Sachs is conducting a “proof of concept” for assisted coding tools powered by generative AI. AI adoption has more than doubled over the past five years, according to a December 2022 survey by McKinsey. According to McKinsey, on average, companies are using roughly four different AI capabilities today.
Yet, many companies are still struggling to capitalize on the full business value that AI can deliver for their organizations. In Deloitte AI Institute’s fifth annual State of AI in the Enterprise research, the number of respondents who call themselves “AI underachievers” increased by nearly a third. While the potential of generative AI is enormous, it “is not without risks,” according to Paula Goldman, Salesforce Chief Ethical and Humane Use Officer and Kathy Baxter, Principal Architect for Salesforce’s Ethical AI practice. However, it is important to recognise that generative AI does not create information in the way you might expect and are familiar with. The way that information is generated has a big impact on the reliability and authority of the response, and how you might use it during your studies. On the surface it may appear that what generative AI tools do is not just a search for information, they also find and present information for you.
Artificial intelligence (AI) and machine learning (ML) have been on the scene for many years, but the arrival of GenAI has changed the game in how consumable AI can be with its ability to produce novel and ‘human-like’ outputs. Salesforce has been exploring how to develop and deploy generative AI to support customer needs for years. For example, the company introduced CodeGen, which democratizes software engineering by helping users turn simple English prompts into executable code. Another project, LAVIS (short for LAnguage-VISion), helps make AI language-vision capabilities accessible to a wide audience of researchers and practitioners.