Shahar Chen, CEO and Co-founder of Aquant, a company focused on delivering generative AI solutions to transform the service industry.
AI technologies, exemplified by tools like ChatGPT and others, have become increasingly influential in both business and society at large, prompting the attention of political leaders and regulators, including the Biden administration and the U.S. Congress.
As AI continues to advance, the need for effective regulations to govern its development and deployment has become more apparent. However, in the process of shaping these regulations, there’s a notable absence: vertical AI vendors. Companies like Microsoft, OpenAI and Meta dominate the regulatory conversation, raising questions about the ethical implications of allowing these tech giants to largely shape the regulatory landscape to their advantage.
The Issue Of Data Privacy
One pressing concern revolves around data privacy. Major players have faced criticism for using data without explicit consent, raising doubts about their ability to craft ethical regulatory frameworks. This leaves the public in a precarious position, wondering if these companies can be trusted to govern AI responsibly when they’ve faced allegations of unethical data practices.
A significant distinction in the AI landscape arises between horizontal large language models (LLMs) and vertical AI solutions. Vertical AI solutions, often provided by smaller, more specialized AI vendors, have a narrower focus. They typically draw data from consented sources and securely store it in dedicated repositories. In contrast, LLMs have faced backlash for utilizing data without explicit consent for training and content generation.
In my experience, vertical AI vendors are exerting double the effort compared to some enterprise technology players in constructing their AI systems. This effort is driven by their commitment to demonstrating the ethical responsibility of their systems and prioritizing data privacy and security. A secured approach guarantees that sensitive data never leaves the confines of the customer’s dedicated repository, emphasizing privacy and confidentiality as top priorities.
The limited interaction with LLMs sets vertical AI apart and makes it an excellent choice for industries dealing with sensitive data, such as medical organizations handling patient information.
Moreover, vertical AI vendors are not only building technology ethically and responsibly but also offering specific expertise and unique perspectives that can substantially contribute to the formulation of effective AI regulations. Here’s why involving technology leaders from these vertical, specialized AI vendors in the regulatory conversation is essential.
1. Diverse Expertise: Vertical AI vendors often specialize in specific AI domains, ensuring that regulatory discussions consider the diverse applications of AI beyond language models.
2. Innovation And Agility: These companies are known for their innovation and ability to adapt quickly to emerging AI trends. Their insights can help anticipate regulatory challenges and adapt regulations to evolving AI landscapes.
3. Avoiding One-Size-Fits-All Regulations: AI is highly versatile, and regulations should reflect this diversity. Vertical AI vendors can provide valuable input to avoid stifling innovation with overly broad regulations.
4. Ethical Considerations: Vertical AI vendors are well-positioned to identify ethical dilemmas unique to their industries, contributing to more comprehensive and ethically sound regulations.
5. Representation And Inclusivity: Involving vertical AI vendors ensures that the interests of a broad range of AI stakeholders are considered, preventing regulations from being dominated solely by large tech companies.
In today’s rapidly evolving technological landscape, embracing AI solutions is vital for organizations aiming to remain competitive. Vertical AI can offer secure options that provide valuable insights without compromising the confidentiality of sensitive information.
While it makes sense to include the major tech players, it’s important to diversify the voices contributing to the AI regulatory conversation by including those vendors that are doing their best to develop ethical and secure AI systems.
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