Implementing the Guardrails for a Responsible Future with AI
Published on : Sunday 02-06-2024
By addressing these key areas, businesses can promote responsible AI usage, mitigate risks, and foster trust among stakeholders, says Abhijit Deokule.
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Recent data from a Gartner survey indicates a significant trend in the business landscape: by 2026, over 80% of enterprises are projected to incorporate generative AI-enabled applications or APIs, a stark contrast to the mere 5% adoption rate observed in 2023. This surge underscores the escalating momentum behind generative AI, marking a pivotal moment in its integration across diverse industries, driving innovation and reshaping operational paradigms.
The impact of generative AI on business processes
As businesses embrace AI on a broader scale, it reshapes not only processes but also revenue models, enhancing overall productivity. However, to ensure the responsible and risk-free adoption of AI, industry stakeholders must carefully evaluate its societal impact, prioritising benefits over potential harms.
Addressing concerns and ensuring ethical AI
While depictions of AI in media like Black Mirror may exaggerate its consequences, legitimate concerns persist regarding its social, political, environmental, and economic impacts, particularly with wider accessibility to generative AI tools.
The unique nature of generative AI necessitates a significant talent shift within enterprises. Despite the growing presence of AI-focused companies, only a small fraction specialise in generative AI. The emergence of generative AI underscores the need for enterprises to revamp their talent pool significantly. A study by Wisemonk reveals that while there are over 29,000 companies in the AI technology sector, only a mere 1% specialise in generative AI.
Prioritising responsible AI: Key focus areas
As AI adoption accelerates and permeates various sectors, it becomes imperative for businesses, governments, and consumers to establish and adhere to responsible AI practices, policies, and standards. Employing a trust-by-design approach throughout the AI lifecycle is crucial for fostering responsible and ethical AI.
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Eliminating human biases
AI systems often perpetuate latent biases present in their datasets, exacerbating both human and systemic biases in real-world applications. Generative AI amplifies this threat, making it imperative to address biases to prevent inequalities across various demographics. Organisations must prioritise fairness in AI by training language models on unbiased datasets, ensuring balanced representation, and eliminating behavioral biases.
Safeguarding data privacy
The quality and integrity of data used to train generative AI systems are paramount for achieving desired outcomes. Inclusion of confidential assets in datasets can compromise user privacy, eroding trust in AI systems and hindering their adoption. To mitigate privacy concerns, companies should prioritise transparency in data usage, implement privacy-by-design principles, and oversee the handling of sensitive personal information from the outset.
Building trust in AI
Given that many AI systems rely on third-party foundational models, ensuring explainability and accountability for system inferences and outcomes is crucial. Businesses must implement robust data management practices and organisation-wide governance to address inaccuracies, enhance transparency, and mitigate legal risks associated with incorrect outputs or IP infringement. Additionally, the autonomy of AI systems poses the risk of inaccurate outcomes or hallucinations, underscoring the need for continuous monitoring and appropriate human intervention to uphold accountability and prevent operational disruptions.
By addressing these key areas, businesses can promote responsible AI usage, mitigate risks, and foster trust among stakeholders, thereby facilitating the ethical and sustainable integration of AI technologies into diverse domains.
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Monitoring AI risks: A global perspective
Given the extensive risks associated with AI systems, particularly with their rapid adoption and pervasive usage across both enterprise and consumer domains, regulatory authorities and government agencies worldwide are vigilant in monitoring emerging threat scenarios and pitfalls. They play a crucial role in driving policymaking initiatives and establishing frameworks to promote responsible AI practices.
This article is attributed to Xoriant.
Xoriant is a Silicon Valley-headquartered digital product engineering, software development, and technology services firm with offices in the USA, UK, Ireland, Mexico, Canada and Asia. From startups to the Fortune 100, the company delivers innovative solutions, accelerating time to market and ensuring clients' competitiveness in industries like BFSI, High Tech, Healthcare, Manufacturing and Retail.
Abhijit Deokule is Xoriant's Chief Operating Officer and a progressive IT industry leader with over 25 years of global experience working with multinational companies across USA and Europe. At Xoriant, Abhijit is responsible for driving the company’s engineering and digital business delivery and operations, executing innovative strategies that ensure operational excellence, successful customer relationships, and amplified growth.
Article Courtesy: NASSCOM Community – an open knowledge sharing platform for the Indian technology industry: https://community.nasscom.in/communities/ai/implementing-guardrails-responsible-future-ai
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