9 most significant problems with generative AI (chart)

Biased results, high cost, copyright infringement, and high energy consumption are the most common problems with the current generative AI tools.

Generative AI, or generative artificial intelligence, is a branch of machine learning that focuses on creating new content, such as images, text, and audio. 

The technology uses algorithms to learn patterns from existing data and then generate new examples that are similar but not identical to the data it was trained on.

The potential of generative AI is incredibly high, but there are several concerns that we should be aware of.

From the Visual Capitalist comes a chart created with cooperation with the Verses, a cognitive computing company building next-generation intelligent systems.

The visual lists the nine biggest problems with generative AI. Among them is the environmental impact of the technology – a result of the high power consumption.

💬 With processing units consuming substantial power, models like ChatGPT cost as much as powering 33,000 U.S. households, with just one inquiry being 10 to 100 times more power hungry than one email.

9 main problems with generative artificial intelligence – here are the highlights:

▸ Bias – Generative AI tools can only produce biased content if they are trained on biased data.

▸ Cost – Training and maintaining generative AI models, like large language model ChatGPT, can be very expensive.

▸ Unclear decisions – Generative AI decisions are often difficult to understand, which can make it hard to hold them accountable or trust their outputs.

▸ Limited input – Generative AI can only produce output that is as good as its training data, so it is important to use high-quality data.

▸ Fake content – Generative AI can sometimes produce false or inaccurate information, even though it seems confident about its outputs.

▸ Intellectual property violation – Generative AI models have been known to use copyrighted or intellectual property without permission or compensation.

▸ Values – Generative AI is not always aligned with human values, and it may not consider the ethical implications of its decisions.

▸ Energy consumption – Generative AI models, like ChatGPT, can use a lot of energy, comparable to powering 33,000 US households per day.

▸ Lack of updates – Generative AI models do not update their knowledge or generate new ideas in real-time, so they may produce outdated or inaccurate information.

Click on the infographic to see it enlarged.

Source: 9 Problems with Generative AI, in One Chart – Visual Capitalist

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