Hyper-tailored AI Communication

The use of a combination of ad-targeting, behavior tracking, natural language processing, and adaptive engagement scripts to target content specific to users. This type of software can aid brands to increase ad relevance and improve return on investment while amplifying customer loyalty.
Technology Life Cycle

Technology Life Cycle


Marked by a rapid increase in technology adoption and market expansion. Innovations are refined, production costs decrease, and the technology gains widespread acceptance and use.

Technology Readiness Level (TRL)

Technology Readiness Level (TRL)

Fully Operative

Technology is operative and demonstrates considerable market competition among manufacturing industries.

Technology Diffusion

Technology Diffusion

Early Adopters

Embrace new technologies soon after Innovators. They often have significant influence within their social circles and help validate the practicality of innovations.

Hyper-tailored AI Communication

A combination of ad-targeting, behavior tracking, natural language processing, and adaptive engagement scripts, advertising used to target content specific to users. By using AI and deep learning algorithms, systems could generate thousands of personalized banners per second, even undertaking the design and rendering of this material, based on an individual’s preferences. At the same time, AI could eliminate error-prone focus groups and disjointed data to bring real-time, relevant insights to help organizations understand, plan, and design better policies for the future. Furthermore, such content could be produced and replicated at an almost limitless scale using the estimated millions of social-media bots.

Via the aggregation of online chatter, regional patterns, and comparative data, it might become possible to predict the demands of ordinary citizens. With these insights, advertising agencies and brands will be able to target specific content such as public services or organizations, or even collect feedback regarding the governmental process. Also, marketing budgets could benefit from this software while reducing some sources of fraud, like click injection or simulated ad clicks. Since AI is trained to recognize actual humans with needs and desires, "spoof" data can be cleaned and rejected.

However, the misapplication of this kind of technology could lead to a scenario of data mediation control and manipulation of information. It would create specific ideology-based bubbles from the perspective of both individuals and entire populations or regions. These populations would be prone to mass data collection for analysis, a process that would directly affect collective autonomy and media independence.

Future Perspectives

In a virtual or augmented world, this technology could provide a unique visual experience for each user, thus shaping how individuals perceive that world. With developed emotional AI, brand avatars might adapt their tone of voice to different profiles by optimizing conversion rates. Members with varying tiers of subscription, for instance, might be able to view the same world differently. A play-for-free member might have to endure advertisements to enjoy certain benefits, while monthly subscription members could roam freely to socialize, play games, and shop.

This can also perpetuate discrimination and reinforce, or even worsen, existing inequalities by making privacy the most magnificent luxury of the new digital era. On the other hand, the development of data analysis methods powered by artificial intelligence and machine learning solutions could be based on an ethical framework. This could create curated content to connect consumers with relevant products and services in line with their interests and lifestyles. As AI becomes more robust within the intersection of psychology and neuroscience, in theory, it could become one of the most advanced and persuasive forms of communication ever invented by humankind.

Image generated by Envisioning using Midjourney

A 2016 review of literature about automation, algorithms and politics identified China as the foremost area in which further research was needed because of the size of its population, the potential for Chinese algorithmic manipulation in the politics of other countries, and the frequency of exportation of Chinese software and hardware. This paper contributes to the small body of knowledge on the first point (domestic automation and opinion manipulation) and presents the first piece of research into the second (international automation and opinion manipulation). Findings are based on an analysis of 1.5 million comments on official political information posts on Weibo and 1.1 million posts using hashtags associated with China and Chinese politics on Twitter. In line with previous research, little evidence of automation was found on Weibo. In contrast, a large amount of automation was found on Twitter. However, contrary to expectations and previous news reports, no evidence was found of pro-Chinese-state automation on Twitter. Automation on Twitter was associated with anti-Chinese-state perspectives and published in simplified Mandarin, presumably aimed at diasporic Chinese and mainland users who ‘jump the wall’ to access blocked platforms. These users come to Twitter seeking more diverse information and an online public sphere but instead they find an information environment in which a small number of anti-Chinese-state voices are attempting to use automation to dominate discourse. Our understanding of public conversation on Twitter in Mandarin is extremely limited and, thus, this paper advances the understanding of political communication on social media.
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