Why do we care so much about authenticity when it comes to AI and marketing?
I vividly recall the first time I dialed a customer support line of a business. The moment I realized the voice on the other end was an automated system, I immediately hung up. A sense of surprise and irritation overcame me, and I dialed again, only to be greeted by the same robotic voice, with its heavy mechanical Mandarin accent. Realizing I couldn’t evade it, I gritted my teeth and waited for it to finish, before curtly requesting a human operator. Only when I was sure I was speaking to a fellow human did I start to relax and explain my issue.
That was many years ago. It was my first, somewhat extreme, natural reaction to the cold, insincere, and impersonal machine. Today, hearing a human voice on a customer service call seems quite surprising, as if to think “Wow, there’s an actual person in the phone.” But I suspect that it’s somewhat comforting.
The Emergence of Artificial Authenticity
Speaking of human-machine conversation, I remember when Apple first launched Siri. I used to try various ways to tease it, driven more by curiosity and entertainment than practical use. As for myself, I never really entrusted Siri with any actual tasks. After a brief novelty period, my iPhone has always defaulted to having Siri turned off.
But why the sudden reference to the odd term Artificial Authenticity? It’s not my original creation. This stems from the real, palpable infiltration of AI into our learning, work, and life. When I tried to precisely search using quotation marks, I discovered there were already discussions about it.
Many online or virtual experiences would likely descend into chaos without the backing of various algorithms. But when these AI applications move from behind the scenes to the forefront, indicating an inevitable future of direct interaction with them, new problems arise. For these uncanny characters, the observations of people online and around me suggest that many people instinctively react with suspect, surprise, awe, shock, and anger… (Of course, there are also positive ones, but that’s not the point of discussion here). What causes those reactions?
What is Authenticity?
To understand why people perceive AI and its outputs as fake, unreal, or suspicious, we first need to examine the definition of authenticity.
Broadly, authenticity is associated with the attribution of genuineness. For instance, what is deemed authentic is often considered real, genuine, or true, while anything not deemed authentic is labeled as phony, fraudulent, or insincere.
Researchers have identified two categories of authenticity:
- Type authenticity involves how well a behavior or object matches up with what an audience expects from a specific category. For example, to decide if a restaurant truly offers Italian or Chinese food, you’d likely consider factors like the ingredients they use, the spices they add, and the taste they deliver.
- Moral authenticity is about how much a behavior or object reflects an observer’s perception of genuine choices, beliefs, or values. While type authenticity focuses on fitting into a certain category, moral authenticity digs deeper: it’s about whether something is truly genuine because it shows real values and beliefs, instead of just going along with societal expectations or other external influences.
These discussions may seem a bit academic, but we will break them down further in a more digestible way later. Nevertheless, it’s crucial to note that the understanding and perception of authenticity is not as simple as it may seem. Typically, we define or judge it based on attributes such as typicality, uniqueness, originality, integrity, or consistency.
Why Do People Care So Much About Authenticity?
Did you notice that people can no longer distinguish between human- and AI-generated texts or pictures? But the moment people realize the work is created by AI, not by human, their perception of its likability and authenticity swings dramatically. Why?
Authenticity perception seems to be less about truth and accuracy with AI. My speculation is that people believe machines lack the ability to be original or unique. Creativity is still deemed a human specialty. Hence, there’s skepticism towards AI, given its opaque working processes or mechanisms, which some still view as a black box.
Moreover, algorithms are distinct from human beings. People still associate machines with the notions of being fake, unnatural, and insincere. Furthermore, when individuals realize they are not interacting with another humankind, but are obliged to collaborate with AI on an equal footing, could they involuntarily link this with their self-concept? Could they perceive this as not being treated genuinely or fairly, leading to a feeling of offense? These possibilities remain unknown.
Topics to be Explored by Au.thenti.city
When I first recognized the concept of Artificial Authenticity and scanned my memory for related psychological knowledge, I didn’t find many direct answers. Perception, trust, influence, decision-making, or self could be relevant topics, but which specifically? I couldn’t provide myself a clear, satisfactory, well-grounded answer, which only deepened my curiosity!
Authenticity is a topic of discussion in many fields, like the authenticity of leaders in organization and management, brands or influencers in marketing, and, of course, discussions on authentic artworks. However, I will primarily probe authenticity in the business and technological contexts, for instance:
- Artificial Authenticity of AI, algorithms, and automation.
- Authenticity in brand marketing, content marketing, influencer marketing, and strategies to improve.
- The psychology behind perceiving authenticity.
If new intriguing topics come up, I will also delve into those. I can hardly wait to embark on these explorations and analyses.
P.S. Since we’re discussing Authenticity, I must confess to avoid any potential offense or loss of trust down the road. My native language is Mandarin, and every piece of word is manually typed by myself. I use an AI tool to learn my writing style from my original texts and output similarly in English. But I still thoroughly review and edit before publish.
Recommended Reading
Carroll, G. R. (2015). Authenticity: Attribution, Value, and Meaning. Emerging Trends in the Social and Behavioral Sciences. John Wiley & Sons, Inc. doi: 10.1002/9781118900772.etrds0020
