We Need to Tell Better Stories About Our AI Future

We Need to Tell Better Stories About Our AI Future

We Need to Tell Better Stories About Our AI Future

Discussions about the ethics, safety, and societal impact of Artificial Intelligence seem to come back to the same cultural touch points found in AI stories that warn of worst-case scenarios. Whether in press coverage or in policy position papers, we keep going back to the same stories. We need to tell more diverse and realistic stories about AI if we want to understand how these technologies fit into our society today, and in the future.

In Kubrick's HAL 9000, the calm assistant shuts Dave out of the system in 2001. In The Terminator, the AI defense system SkyNet becomes self-aware and initiates a nuclear holocaust to decimate the human race. In Ex Machina, the AI sex robot becomes self-aware and passes the new Turing test by convincing the human to empathize with her and help her escape.

These prominent AI stories pit man versus machine, relying on one of the most fundamental examples of narrative conflict to move the story forward. It's not surprising that stories we tell tend towards this form—that we should position ourselves as the protagonist and pit the AI technology in opposition as the antagonist. 

Read Also:
This Startup Wants to Help Brands Make Videos Using Artificial Intelligence

At first glance Minority Report also reads like another man versus machine story, but on closer reading the conflict lies less in understanding or exposing the pre-cog technology itself, than in confronting and escaping the society that implements this deterministically judgmental technology. The technology is the catalyst for action but the real conflict of Minority Report lies between man and the state, or man versus society.

If we continue to rely on these sci-fi extremes, we miss the realities of the current state of AI, and distract our attention from real and present concerns. 

But within the AI technology industry, the story arc follows a different pattern. It's less a conflict between man and the technology and rather a conflict between man versus himself. The highly publicized and celebrated benchmarks of progress in artificial intelligence focus on ways that man (that is, engineers) have built systems that are capable of beating humans at ever more complex and subtle challenges: from games of strategy like StarCraft and Go, to feats of knowledge and language parsing in the subtle play of language and puns of Jeopardy. While the technology competes against expert players, these moments are really about celebrating an engineering achievement that bests man at his own game. It's no wonder that the AI engineering community doesn't take kindly to discussions that start with nods to Terminator and Minority Report. The AI community is more interested in its own hero narratives that accomplish the impossible task of reproducing intelligent behavior.

Read Also:
8 Business Process Analytics Every Manager Should Know

So why do these AI narratives matter? These stories are the reason we are having conversations about AI accountability, but they are also grossly oversimplified, and fall into the trap of narrative fallacy. We end up using them as shorthands and heuristics to guide our conversations and decision making, when they are extreme and perhaps focused on the wrong points of conflict.

The public perception created by these hollywood narratives arguably leads to efforts like the Partnership on Artificial Intelligence to Benefit People and Society. A partnership between Facebook, Google, Amazon, IBM, and Microsoft, the group aims to address and get beyond these inescapable associations. In their mission statement, they write: "We believe that it is important for the operation of AI systems to be understandable and interpretable by people, for explaining the technology." In stating that, "With artificial intelligence, we are summoning the demon," Elon Musk has evoked the most primordial narrative of all: the fight between good and evil. But what if we're getting the narrative wrong? 

Read Also:
Big data problem? Don't forget search

But if we continue to rely on these sci-fi extremes, we miss the realities of the current state of AI, and distract our attention from real and present concerns.



Read Also:
What artificial intelligence will look like in 2030
Read Also:
4 Steps to Designing and Launching an Effective Data Product
Read Also:
Artificial Intelligence Is Setting Up the Internet for a Huge Clash With Europe
Read Also:
Intel's transition to the Internet of Things is necessary, but costly

Leave a Reply

Your email address will not be published. Required fields are marked *