Will Multinational Companies Shape Public Thought through Generative AI?
The rise of generative AI has brought about remarkable advancements in how we access information and learn. Conversational queries, powered by technologies like Chat GPT or Gemini, have enabled natural language conversations, revolutionising our ability to explore and understand complex topics. As we delve into this evolving landscape, I want to examine an intriguing future scenario in which multinational companies leverage Generative Artificial Intelligence (GenAI) mechanisms to influence the way people think and elevate their brand presence. This speculative narrative demands thoughtful consideration, given its potential, plausibility, and even probable implications. How can we take proactive measures to shape this scenario in a manner that aligns with our collective goals and values?
Generative AI at the intersection of innovation and risk perception through speculative design
Generative AI, with its ability to generate complex and creative outputs, has already emerged as a powerful tool across diverse domains such as art, content creation, music, finance, research, human-computer interaction and marketing. These intelligent systems are trained on vast amounts of data; they can predict patterns and generate content that closely mimics human creativity. The potential for (positive and negative) societal impact through Generative AI is immense, so it is crucial that we also acknowledge the inherent risks that this technology presents.
Speculative design offers a compelling approach that allows us to explore and understand the potential consequences of emerging technologies like Generative AI. By combining creativity and critical thinking, it encourages us to contemplate alternative futures and question existing paradigms. Speculative design puts us in a tangible framework that enables us to comprehend the risks and consequences associated with an application, envision possible trajectories, provoke dialogue, and make ethical decisions.
Influence-based business models
My speculative exploration considers, as key factors, the significant growth witnessed in emerging Gen AI model enterprises and revenue generation strategies employed by influential technology giants like Google and Meta. These two Big Tech firms base their revenue streams by offering monthly subscription options that provide users with ad-free experiences on their platforms. For example, Meta recently launched an ad-free paid model in Europe, offering users the option to subscribe for an uninterrupted platform experience on Instagram and Facebook.
What if Generative AI model companies started to adopt similar business models? What will be the implications and potential transformations for businesses and our society? Here are a couple of trajectories that could emerge.
GenAI as a competitive advantage (B2B)
On the B2B front, GenAI could serve as a basis for a business model where companies pay to enhance the visibility of their data. By paying, companies can strategically position their content and responses on GenAI platforms, ensuring that their values and offerings are prominently displayed when deemed relevant to a user’s query. Generative AI models would generate revenue by allowing companies to make their data more prominent than their competitors’.
With this model, the competitive landscape would be further intensified, as companies vie to showcase results aligned to their brand values and offerings during user queries. Here, businesses would be leveraging Generative AI to influence public perception and elevate their brand presence.
As companies strive to make their data more prominent through financial investments, there is a risk that the authenticity of information may become compromised. In a bid to outshine competitors and gain a competitive edge, businesses might be inclined to prioritise promotional content over factual accuracy. This could result in a distorted view of information presented to users, potentially undermining the reliability of the AI-generated recommendations and responses (Image 1).
Freemium plans for unbiased AI results (B2C)
In the same scenario, GenAI platforms could offer different tiered services to individuals: a premium plan, a basic plan and a free plan (Image 2).
A premium plan would provide users with exclusive access to AI-generated results that remain completely unbiased from advertising. By paying a subscription fee, individuals gain the ability to leverage AI-generated insights that are free of the manipulative influences a brand’s interference would have on the information they receive.
A basic plan, instead, would still provide unbiased results, but they may still feature sponsored content that subtly promotes specific products, or services aligned with the platform’s advertisers.
In contrast, a free plan would grant users access to AI-generated results. However, these results may rely on a very basic knowledge base heavily driven by advertisers and the output would be influenced by biases introduced through advertising, with factual inaccuracies.
From an anesthesised future to a possible (plausible? probable? preferrable?) reality
As you can see, by exploring the intersection of innovation and risk perception through a speculative design lens, we can better understand the potential implications and shape its trajectory in a way that aligns with our shared goal of serving society and help us develop services that respond to users’ needs.
Following this approach, we analysed the scenario in which Gen AI model companies use a freemium advertising-supported model, and companies subsidise the availability of AI-generated outcomes to the public based on the selected tiered-product offering. Foreseeable repercussions of this might involve advertisements shaping the information presented to users.
In this context, the power to influence the way people think falls in the hands of those corporations capable of investing substantial amounts of their data in Generative AI models.
Personally, I believe that the balance between commercial interests and the preservation of authenticity is crucial to ensure that, as citizens, we receive reliable and truthful information.
In this sense, regulatory frameworks and industry standards should be established to govern the use of Generative AI in a way that safeguards the integrity of information and protects the interests of users, as well as the broader public. Therefore, it is key to implement regulations at a global level to ensure transparency in advertising practices that builds trust with audiences, establishes ethical guidelines for the use of Generative AI models, and prevents the spread of manipulation and misinformation caused by advertising influences. The transparent disclosure of AI-generated content versus advertisements is necessary.
In parallel, we should keep promoting user education and awareness about the influence of AI-generated ads to empower informed decision-making. Collectively, we must acknowledge the ethical imperative to counteract the bias that ambiguous business advantages can create, if we are to design a basis that fosters a more equitable digital environment. Let’s make sure to embrace this challenge head-on.
