The Erosion of Reality In The Age of Artificial Intelligence
There was a simpler time when witnessing an event with one’s own eyes offered a definitive seal of reality. Hearing a familiar voice unequivocally confirmed a genuine presence, and news arrived through established, reputable channels that at least strived for a degree of balance. That uncomplicated world is now decisively gone.
Sure, people might disagree with each other, but there was at least a shared sense of what counted as real. Over the past decade, we have clearly noticed how that shared ground has thinned as information now travels faster than we can process it. Public conversations have become messy, reactive, and heavily influenced by the agendas of people who know how to shape a narrative for attention or effect.
Now, with the arrival of advanced AI tools, this environment has grown even more complicated. It’s now almost effortless to create something that looks and sounds real without needing any real event behind it, and that changes how people understand the world around them. Before AI became widely accessible, the truth was already under pressure. Social media has always had the tendency to reward exaggeration, shock, and conflict, but when news outlets began competing for engagement rather than depth, influencers quickly learned that dramatic or emotional content performs significantly better than carefully verified information.
Once these habits were established, AI technology continued to perpetuate them. It supercharged them by becoming easy for anyone with motivation to produce content that looks credible enough to mislead a large audience.
A simple example is a fabricated video of a public figure making an inflammatory statement. The clip appears online, gains momentum, and starts to influence conversation before anyone has even had the chance to verify it. Even if later revealed as synthetic, the impact never fully disappears. People remember their emotional reactions more easily than the correction, and the emotional residue creates a quiet hesitation the next time they encounter anything in a remotely similar category.
This hesitation is subtle but meaningful because trust relies on confidence in what we perceive. Deepfakes and voice clones have made deception incredibly accessible, as tools that once required specialised skills are now designed for unmitigated convenience. A teenager can create a convincing fake. A scammer can reproduce a loved one’s voice within minutes, or someone with political intent can easily release a video built purely to create fear or confusion. These scenarios are happening in real time, and we are seeing the effects in the way people react to the information they are so blindly fed.
Families have fallen victim to cloned-voice scams, activists have discovered synthetic recordings of themselves circulating online, and professionals in finance, politics, and public communications now have to build an extra layer of security and multiple verification processes around content that once would have been seen as undeniable proof. The low barrier to creating these fakes has made public trust far more fragile than it used to be.
Another layer of complexity comes from AI-generated chatbots and automated accounts designed to simulate human participation. These bots can comment, argue, agree, provoke, and amplify narratives at scale. They create the illusion of consensus or outrage, making certain views appear more popular or credible than they truly are. In many cases, engagement itself is manufactured. People are often responding to machines without even realising it, which further distorts perception and undermines confidence in what feels like public opinion.
So when trust weakens, society inevitably absorbs the impact, and people start doubting everything they see, including information that is legitimate. The constant pressure to verify every detail creates a type of exhaustion. Some have described it as mistrust fatigue. It becomes difficult to know which sources deserve confidence.
Some people choose to disconnect entirely from the news. Others choose a narrow set of voices that simply confirm what they already believe. This leads to isolation, polarisation, and the sense that everyone lives inside their own information bubble.
Now, add the role of social media algorithms, which deepen this divide. Two people can watch the same video but see completely different commentary beneath it. One might see sympathy and support, while the other sees hostility and outrage. Each person walks away believing that their interpretation reflects the wider public, even though the platform is only showing them what it predicts they will engage with. Over time, these customised information streams build separate realities that rarely meet each other in the middle.
Platforms like Truth Social or X present themselves as champions of truth, but often fall into the same patterns. They draw in people who are angry, afraid, or searching for certainty. They amplify content that captures attention rather than content that offers clarity, while automated accounts, engagement bots, and coordinated messaging add another layer of distortion, as repetition and volume can easily be mistaken for credibility. These environments reward visibility and confidence, and not accuracy.
Living in a climate like this changes how people think about truth. Instead of something we recognise together, it becomes something we select based on identity, community, or convenience. This shift affects how we discuss important issues, hold leaders accountable, and build relationships. It becomes harder to trust others and harder to find common ground when everyone believes their version of events is the only real one.
Even so, truth is not gone. It simply requires more intentional effort than before. The tools that help us navigate this environment are simple, though not always easy. They include slowing down before reacting, checking more than one reliable source, asking questions instead of assuming, noticing emotional triggers, and choosing conversations that prioritise understanding over winning. These practices strengthen critical thinking and help separate fact from noise.
This is also where tools designed to support discernment, rather than dictate conclusions, begin to matter. New and revolutionary platforms like the Truth Seekr App are not about replacing judgment, but rather encouraging better habits by prompting users to question sources, assess credibility, and reflect before sharing. They support a more deliberate relationship with information. Guidance models like Truth Seekr Coach extend this approach by helping individuals recognise bias, emotional reactivity, and the influence of artificial engagement. The value lies in learning how to think more clearly, not in being told what to believe.
The world has changed quickly, and the responsibility to find truth now rests more heavily on the individual. That reality can feel demanding, yet it also creates space for growth. When we treat truth as something worth working toward, we build stronger habits and regain agency in how we engage with information.
Deception will always exist, but it cannot replace reality. It simply demands that we approach what we consume with more care and less complacency.
In a time when almost anything imaginable can be fabricated, the simplest and most reliable tools we have are curiosity, patience, and discernment. These qualities help us step back from the noise, including artificial engagement and automated influence, and see information for what it is rather than what it claims to be. They give us the steadiness to navigate uncertainty and the judgment to evaluate before reacting.
Most importantly, this approach affirms that truth still matters. The effort we put into understanding what is real sharpens our own thinking and strengthens the society we all share responsibility for sustaining.
Written by Claire Taylor in collaboration with Roy Fletcher