Deepfakes are AI-generated media that can mimic real people’s appearances and voices. These have rapidly evolved from a technological curiosity to a significant force which reshape digital business models. Nowadays deepfakes offer a wide range of commercial applications from personalized advertising and virtual influencers to content creation and customer service automation (Herbert Smith Freehills, 2024; Ferraro et al., 2024). However, as the technology advances this brings complex ethical especially about misinformation.
Digital business models are using deepfake technology to innovate and enhance customer engagement. Companies are exploring virtual influencers who engage with audiences and offer brands a new way to connect without the use of human influencers. Deepfakes also play a role in personalized marketing where tailored AI driven content creates more compelling advertisements. However, the rise of deepfakes goes hand in hand with ethical challenges. Which includes concerns about authenticity, consent, and misuse. As businesses adopt these technologies, they must carefully consider the potential risks alongside the opportunities.
Ethical challenges connected to the use of deepfakes are significant and particularly now when digital transformation spreads across industries. A major concern is the use in spreading misinformation such as deepfake videos of politicians on big social media platform like Meta and X. This as a result can have an undermining impact in public figures and institutions. Additionally, deepfakes involve consent and privacy issues. This because the media can be created and shared without the permission of an individual. Therefore, companies aiming or using this new technology must implement ethical guidelines that clearly label synthetic media and do their utmost best to prevent misuse and consent violations.
As deepfakes influence digital business models companies must balance innovation with responsibility. While deepfakes offer immense potential in marketing, entertainment, and customer engagement, they also pose significant risks. Companies need to explore these opportunities but must also set ethical standards and develop safeguards to protect individuals and society. The future of deepfakes in business depends on leveraging their potential while carefully managing ethical implications.
Deepfakes in advertising – who’s behind the camera? | Herbert Smith Freehills (2024). https://www.herbertsmithfreehills.com/notes/tmt/2024-02/deepfakes-in-advertising-whos-behind-the-camera
Ferraro, C., Demsar, V., Sands, S., Restrepo, M., & Campbell, C. (2024). The paradoxes of generative AI-enabled customer service: A guide for managers. Business Horizons, 67(5), 549–559. https://doi.org/10.1016/J.BUSHOR.2024.04.013
Hi Jurre, thank you for your blog contribution!
You posit an interesting take on how business models are reshaping due to emerging deepfakes.
I remember the first time I saw a deepfake, or at least when I recognized it as one. It was an obvious scam video where Elon Musk appeared to be sitting in on a podcast, promoting a new idea of his: pay him 1 bitcoin, and he would double it.
Even though I knew it was a scam because of the obvious money-doubling scheme, his voice, face, and demeanor looked so genuine that I wondered if anyone had fallen for it.
Another development I read about recently is that criminals are starting to wear fake fingers in public settings. They hope to defend themselves in court by claiming that the video made of them is a deepfake, allowing them to potentially escape prosecution.
I wonder how we are going to differentiate between real and fake in the close future from now..
This is an interesting take on deepfakes and how they influence businesses. The opportunities of the deepfakes seem to be very exciting, especially for marketing purposes and customer service. However, I agree with you that the potential ethical downside is huge. Misinformation (in written form) has already been a problem in the past and I think that by adding the visual and audible dimensions misinformation appears to be even more credible.
A service/bot on your devices that can detect deepfakes would actually be a nice layer of protection against deception. This tool could help users distinguish between authentic and synthetic media, providing more transparency in an era where deepfakes are becoming increasingly realistic. I do not know if a service like this already exists and is feasible but I think (if it does not exist yet) this would be a great business opportunity.