How No-Code AI Brings Both Massive Benefits and Risks

For those with little to no experience with computer science, the notion that they can use artificial intelligence may seem doubtful. However, developments in AI have made it possible for those with limited knowledge and resources to implement AI in their businesses. Today, non-coders and small businesses with minimal funding can utilize AI to their advantage.

There are a number of “no-code” platforms available to consumers which enable the use of AI without also using a programming language. Such products typically allow users to drag and drop icons to set up an algorithm. Many of these platforms are produced by startups such as Akkio, which allow users to create algorithms that analyze data, or Juji, which can create chatbots. These platforms are designed to be used by people without coding experience, which means that putting them to use can feel like putting together the pieces of a simple puzzle.

Despite the ease with which no-code AI platforms can be implemented for practical applications, there are still potential drawbacks which must be considered by those considering whether or not to do so. The market for no-code AI platforms is dominated by startups, some of which are unproven and may be of lower quality. For example, some AI platforms are more accurate than others, which means a potential user would want to test the platform  before fully integrating it with their business. Potential users should also have a clear idea of what they want their AI platforms to do; while these users don’t need to know how to code, they still need to understand the impact of these platforms and how exactly they will further their business needs.

There are also ethical issues surrounding no-code AI platforms, particularly in the context of AI being widely available to those who might not consider ethical implications whatsoever. AI has historically been dogged by problems with bias and privacy and these problems still remain. Putting AI into the hands of people who lack a strong understanding of  these issues might in turn amplify these problems. For example, a business that does not have a racially diverse consumer base might demonstrate racial bias issues with an AI algorithm. Another possibility is a small business or startups without proper cybersecurity infrastructure suffering a data breach.

While bias and privacy issues are concerning, companies have already begun to  implement policies which appear to effectively mitigate these risks. For example, c3 AI, a company that produces no-code AI platforms provides training to users who want to implement the company’s products in order to educate these users about the potential issues associated with AI. eBay is another company that has taken steps to fight these issues; eBay only allows no-code AI platforms to be used in low-risk situations where bias or privacy issues do not exist. These endeavors seem to be reasonable and effective, but they are not necessarily standardized across the entire industry. Some sort of standardization appears to be necessary, whether through government policy or market forces, if no-code AI is going to be widespread without significant issues.

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