An important part of ethical problems is the the proliferation of bots on the Internet. Their activity reduces the level of security when communicating on social networks; the credibility of the media and public speakers loses importance. The consequences of the work of bots contributed to the development of programs and algorithms to identify artificial accounts. Nevertheless, the effectiveness of such security tools remains understudied.
Cyber ethics generally refers to the rules of moral behavior in the Internet environment. It extends beyond network etiquette, the rules developed in the early days of Internet use. Most authors note issues related to crime, safety and security, privacy, and personal freedom. One of the main issues of Internet ethics is the use of bots in social networks. A bot is a program automatically or automatically performs certain actions in social networks instead of a human user. For example, putting “Like” marks, sharing information on the blog, and so on. A bot is not an account in and of itself, but fake accounts have become known as such. Millions of user accounts were created and managed by such programs, indistinguishable from the accounts of ordinary users. All social networks on the Internet were flooded with bots, which in some cases, account for up to a third of all active users.
Whatever the purpose served by the use of bots, its main feature is that it discredits the Internet as a means for free communication, distribution of relevant and authentic information, a platform for commercial and noncommercial activity, and undermines the principle of mutual trust of all participants of an interaction. The problem with identifying bots on social networks has two aspects: to identify bots, it is necessary to work only with publicly available information about users’ accounts, and the probability of mistaken definitions must be kept as low as possible.
The proliferation of bots is associated with the fact that every year the economic and social importance of social networks grows. In 2015, U.S. residents spent 2.5 hours a day using various social networks, compared to a global average of 2.4 (Griffin et al., 2021). This year, social media usage statistics have almost doubled (Griffin et al., 2021). At the same time, the share of bots in the functioning of applications for communication has increased by 50% (Shao et al., 2018). Information in social networks spreads from person to person; the user, after reading the post, expresses his opinion or shares this information with other users. As a rule, the spread of posts on social networks has an avalanche effect, the greater the response from users, the greater the spread (Shao et al., 2018). This feature of social networks is exploited with the help of bots to unfairly promote goods and services, popularize certain people, plant points of view, and propagate ideas. This is the most glaring ethical problem associated with the use of bots. The latter, by planting false beliefs, form a false picture of the world, misleading users about global issues.
The most typical picture of the use of bots is presented on Twitter. As the number of bots increased, the company began introducing software to identify bots. It was found that there were 50 bots for every 200 users, which is an alarming statistic (Shao et al., 2018). After a number of studies, some neural network algorithms were introduced that analyzed each profile according to special criteria and determined if it was a bot.
In my opinion, introduction of bots is a global cyber-ethics problem. It decreases the level of trust and sincerity of people, provokes aggression and intolerance. Many companies are trying to address the issue of reducing the number of artificial accounts, but neural network algorithms are not yet effective enough. The problem of detecting bots from social networks is related to the question of how to increase the accuracy of bot detection to the highest possible level, which demands further researches and studies.
References
Griffin, M., Martino, R. J., LoSchiavo, C., Comer-Carruthers, C., Krause, K. D., Stults, C. B., & Halkitis, P. N. (2021). Ensuring survey research data integrity in the era of internet bots. Quality &Amp; Quantity, 56(4), 2841–2852.
Hurlburt, G. (2018). Toward Applied Cyberethics. Computer, 51(9), 80–84.
Shao, C., Ciampaglia, G. L., Varol, O., Yang, K. C., Flammini, A., & Menczer, F. (2018). The spread of low-credibility content by social bots. Nature Communications, 9(1).