Beyond Black Mirror: AI, user experience, and ethical concerns in the future of TV

Television is set to change

The undeniable rise of artificial intelligence (AI) presents vast possibilities for the television industry.

Inspired by the Black Mirror episode "Joan is Awful," this article delves into the profound implications of AI in TV. We explore its impact on user experiences and examine the ethical considerations it brings to something we’ve all come to know and love; television.

AI and dystopian futures

Imagine a world where the boundaries between reality and fiction blur, as portrayed in the Black Mirror episode "Joan is Awful." In this episode a service similar to Netflix invades the life of Joan by using AI to create an AI-generated series called "Joan is Awful," unveiling her personal struggles in almost real-time. As the show goes viral, viewers worldwide witness the unravelling of Joan's life, leading to devastating consequences.

Of course, "Joan is Awful" is fictional. However, the episode serves as a cautionary tale, sparking crucial questions about the future of TV. So, without further ado, let’s explore the potential applications of AI in the TV industry, with a focus on user experience and the trade off between innovation and privacy.

1. Personalised content recommendations

One way AI enhances the TV viewing experience is by providing personalised content recommendations. Utilising user preferences, viewing history, and behaviour patterns, algorithms curate tailored suggestions that cater to individual tastes. This ensures viewers are presented with relevant and engaging content, enhancing their overall satisfaction and saving time spent searching for shows or movies.

However, while AI makes an infinite amount of content easy to access, there’s a concern that this personalised approach comes with the risk of failing to expose users to content beyond their viewing patterns. This could limit users to familiar content, while hindering exposure to fresh and exciting shows. The question would then be how can AI help me discover something new which I might love?

2. Enhanced content discovery: find something new

This is where AI-powered algorithms could contribute further to content discovery, enabling users to explore a range of options beyond their usual preferences. By leveraging machine learning techniques, TV platforms can analyse vast amounts of data to identify content similarities, themes, and genres. This allows users to discover a diverse range of new shows that align with their interests, fostering a sense of exploration and serendipity.

Nevertheless, this content, although different, may still fail to inspire viewers, or satiate their appetite for the unknown. It could also create algorithmic bubbles like we see on social media platforms where, although exposure is broad, it still falls within safe, acceptable themes, potentially neglecting to inspire viewers to venture into truly unexplored territories.

3. Real-time audience engagement changing the narrative

The integration of AI technologies opens up new possibilities for real-time audience engagement. Think the ‘red button’ or ‘phone lines’ but in real time with more interactive and immersive features, such as live polls, trivia or even viewer-driven changes to narratives. This could encourage active participation and shape the content they consume making for more dramatic twists and turns or happier resolutions where preferred.

This immersive experience not only deepens the connection with the TV show but also provides valuable insights for content creators, enabling them to gauge audience reactions and preferences. Real-time shopping through product placements and advertisements is also an exciting prospect.

4. AI-generated and directed content

As AI advances, the potential for AI-generated content becomes increasingly relevant. Automated scriptwriting, virtual actors, and AI-assisted storytelling are emerging concepts that could revolutionise TV production. Users may have the opportunity to input real-world elements like the time, weather, or even themselves or others they know, creating personalised, situational shows that are perfect for them in that moment. This technology could democratise TV and film creation, empowering everyone to become directors and potential influencers.

While this technology offers exciting creative opportunities, questions arise concerning intellectual property, artistic integrity, the role of human creators, and the extent of AI’s creative capabilities.

Ethical and privacy considerations

While AI offers tremendous potential for TV entertainment and holds great promise, they must address ethical and privacy concerns. Utilising personal data, such as viewing habits and user interactions, to fuel AI algorithms raises questions about consent, transparency, and data security. Implementing user-based controls, enabling quick and easy opt-out or algorithm alteration based on life changes or circumstances, is crucial. The loss of a loved one is a prime example of this.

The implications of AI in the TV industry have been brought into focus in recent weeks, with the ongoing Hollywood actors' strike. Concerns about AI's increasing capabilities leading to virtual characters endangering actors' roles and livelihoods are at the forefront of the strike.

Transparent AI decision-making

To combat concerns around AI bias and decision-making opacity, prioritising transparency in AI systems is essential. Users should have a clear understanding of how AI algorithms shape their content recommendations and be empowered to customise their data sharing preferences. Opt-in consent mechanisms should be the norm, empowering users to make informed decisions about how their personal information is used.

The AI-Integrated Future of TV

The future of TV entertainment is intricately intertwined with AI, promising exciting opportunities to elevate user experiences, revolutionise content creation and foster greater audience engagement.

However, as AI becomes more deeply integrated into our media consumption, it’s vital to address the ethical and privacy implications that arise and carefully monitor the impact of these changes on the quality and consumption of the content. Much like how we’re seeing people turn off from smart devices and ‘detoxing’, could we see user preferences shift back to authentic non-AI generated content in response to too rapid a push or a loss of interest in it before we start to realise some of its other possible futures?

One unresolved question is how these developments will impact major players in the TV and entertainment industry. As entertainment becomes infinitely composable and ultimately in users’ control, media spend, production houses, and entertainment brands will need to adapt to this evolving landscape.

It’s crucial to prioritise transparency, user control, and responsible data practices. The TV industry can embrace AI as a powerful tool to enhance user experiences while upholding the values and integrity that have made TV such an enduring form of entertainment.