2019 is well under way and the attention on Artificial Intelligence persists. An AI revolution is already underway (for a very informative deep dive on this topic check this infographic). Businesses are investing heavily in the field and staffing up their data science departments, Governments are releasing AI strategy plans and the media continues to churns out fantastic stories about the possibilities of AI. Beyond that, discussions about ethics and appropriate uses are starting to emerge. Even the Vatican is paying attention. What could go wrong?
If history is any guide, we have been through an AI spring before only to see it fall into an AI winter. In the mid 80’s, the funding dried, government programs were shut down and the attention moved on to other emerging technologies. While we live a different reality, a more globalized and connected world, there is no guarantee that the promise of AI will come to pass.
In this blog, as an industry insider and diligent observer, I describe factors that could derail the AI revolution. In short, here are the things that could turn our AI spring into another bitter winter.
#1: Business Projects Fail to Deliver
Honestly, this is a reality I face everyday at work. As a professional deeply involved in a massive AI project, I am often confronted with the thought: what if it fails? Just like me, hundreds of professionals are currently paving the way for an AI future that promises intelligent processes, better customer service and increased profits. So far, Wall Street has believed the claim that AI can unlock business value. Investors and C-level executives have poured in money to staff up, upgrade systems and many time re-configure organizations to usher in an AI revolution in their business.
What is rarely talked about is the enormous challenges project teams face to transform these AI promises into reality. Most organizations are simply not ready for these changes. Furthermore, as the public becomes more aware of privacy breaches, the pressure to be innovative while also addressing ethical concerns is daunting. Even as those are resolved, there is the challenge of buy-in from internal lines of business who can perceive these solutions as an existential threat.
The significant technical, political and operational challenges of innovation all conspire to undermine or dilute the benefits promised by the AI revolution. Wall Street may be buying into the promise now but their patience is short. If AI projects fail to deliver concrete results in a timely manner, investment could dry up and progress in this area could be significantly halted. If it fails in the private sector, I can easily see this cascading into the public sector as well.
#2: Consumers Reject AI-enabled Solutions
Now let’s say the many AI projects happening across industries are technical and organizational successes. Let’s say they translate into compelling products and services that are then offered to consumers all over the globe. What if not enough of them adopt these new products or services? Just think about the Segway that was going to revolutionize mobility years ago but never really took off as a mass product. Adoption always carries the risk inherent in the unpredictable human factor.
Furthermore, accidents and business scandals can have a compounding effect on the public opinion of these products. One cannot deny that the driverless car pedestrian fatality last year in Arizona is already impacting its development possibly delaying launches by months if not years. Concerns with privacy threaten to erode the public’s confidence on business usage of data which could in turn further hamper AI innovation.
Technology is advancing at neck-breaking speed. Can humans keep up and even more importantly, do they care to? For the techno-capitalist, the human need for devices is endless. They spread this message through clever marketing campaigns. Yet, is everyone really buying it? AI-enabled products and services can only succeed if they are able to demonstrate true value in the eyes of the consumer. Otherwise, even technical marvels are destined to fail.
#3: Governments Restrict AI Innovation Through Regulation
Another factor that could derail the AI revolution is government regulation. It is important to note that not all regulation is harmful for innovation. Yet, ill-devised, politically motivated, reactive regulation often does. This could come from both sides of the political spectrum. Progressive politicians could enact burdensome taxes on the use of AI technology discouraging its development. Conservative could create laws siding with large business interests that choke innovation at the start-up level.
Emerging technologies like AI are currently not front-end center topic in elections. This can be a blessing in disguised as it is probably too early to create regulatory apparatus on these technologies. Yet, that does not mean government should not be involved. Virtuous policy should bring different stakeholders to the table by creating an open process of discussion and learning.
With that said, governments all over the world face the challenge to walk the delicate balance between intervention and neglect. Doing this well is very context-dependent not lending itself to sweeping generalizations. Yet, it must start with engagement. It was shocking to see US lawmakers’s ignorance of social media business models demonstrated in recent hearings. That gives me little hope they would be able to grasp the complexities of AI technologies. Hopefully, a new batch of more tech-savy lawmakers will help.
#4: Nationalism Hampers Global Collaboration
The development of AI thrives on an ecosystem where researchers from different countries can freely share ideas and best practices. A free Internet, a relatively peaceful global order and a willingness to share knowledge have so far ensured the flourishing of research through collaboration. As Nationalist movements rise, this ecosystem is in danger of collapsing.
Another concerning scenario is a a geopolitical AI race for dominance. While this can incentivize individual nations to focus their efforts on research, it can also undermine the spread and enhancing of AI technology applications. A true AI revolution should not be limited to one nation or even one region. Instead, it must benefit the whole planet less it becomes another tool for Colonialism.
On the one hand, regional initiatives like the European Union’s AI strategy are a good start. The ambitious Chinese AI strategy is concerning. The jury is still out on the recently released US strategy. What is missing is an overall vision of global collaboration on the field. This will most likely come from intra-governmental organizations like the UN. Until then, nationalist pursuits in AI will continue to challenge global collaboration.
Conclusion
This is all I could come up, a robust but by no means an exhaustive list of what could go wrong. Can you think of other factors? Above all, the deeper question is, if we these factors derail the AI revolution, would that be necessarily tragic? In some ways, this could delay important discoveries and breakthroughs. However, slowing down AI development may not be necessarily bad as conversations on ethics and public awareness is its beginning stages.
In the history of technology we often overestimate their impact in the short run but underestimate it in the long run. What if the AI ushers no revolution but instead a long process of gradual improvements? Maybe that’s a better scenario than the fast change promised to business investors by ambitious entrepreneurs.
