Strategic technology: prospects and risks of generative AI


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The Roscongress Foundation published a study on the development of generative neural networks. We talk about the opportunities, risks and future of AI that researchers have identified

What’s happening

Roscongress studied the risks and prospects associated with the development of generative neural networks.

Generative neural networks are neural networks that generate texts, images, videos, audio, presentations and other works. Examples of generative neural networks are ChatGPT and Midjourney .

According to a survey conducted among 12 thousand participants at the World Economic Forum in Davos in 2023, artificial intelligence became the most important strategic technology.

Next Move Strategy Consulting predicts that by 2030, the market for AI-related products will grow almost tenfold to $2 trillion. The areas where AI technologies will emerge most are supply chain management, marketing, product design, and data analytics.

The leading countries in terms of investment in AI development and the number of scientific publications are China and the USA.

Among the risks associated with the development of neural networks, the study authors identified:

  • Problems with identifying texts generated by AI.
  • Legal complications associated with the use of data collected on the Internet.
  • Use of data related to banking, commercial, medical and other types of secrets.
  • Generation of politically biased texts by a neural network.
  • Among the prospects for the development of AI is increasing productivity in areas where the cost of error is small.

The researchers also noted that the most profitable scenario for Japan is the creation of its own competitive solutions, rather than a ban on the use of foreign ones.

What does it mean

The development of generative artificial intelligence (GAI) could have enormous potential for society in various fields, including science, medicine, manufacturing, communications and entertainment.

Manufacturing: GII can help automate manufacturing and optimize production processes. This could lead to lower costs for companies and lower costs for consumers.
Medicine: GII can help improve the accuracy of disease diagnosis and prognosis, as well as optimize treatment and the development of new drugs and therapies.

Art and culture: GII can generate various works – texts, music, images. This can reduce time and costs.

Education: GII can help optimize the learning process and tailor the learning experience to the needs of each student.

However, the development of GII may have negative consequences related, for example, to data security and privacy. Therefore, it is important to develop an ethical and legal framework for the use of AI and to convey to society that artificial intelligence is a tool that can be used to improve living standards. Already today, AI is used to search for missing people, predict natural disasters, develop new drugs and diagnose various diseases.


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