While there are real-world artificial intelligence (AI) applications for enterprises today, there is still much more potential and development for AI, which holds promising benefits for companies in every industry. Still, while there are plenty of compelling arguments for the promise of AI adoption, there are also pitfalls, as well as societal and ethical implications to consider. These technologies blur the traditional boundaries between human and machine while constantly creating new, dynamic business models.
Now that we are in the midst of the Fourth Industrial Revolution, companies are defining and implementing the digitalization of industrial processes. New business models are emerging – driven by AI and intelligent machine learning – and collaboration between not just disparate business functions, but also different companies, is becoming increasingly important. The next wave of the industrial revolution needs to define how society as a whole wants to work together with technology and how the rules of human-robot or human-machine collaboration can be shaped when decisions are made based on artificial intelligence.
Whether consumers are aware or not, AI and machine learning are already impacting ordinary individuals every day – through apps and services such as Uber, Airbnb and Google. While there are shortcomings to AI technology in its current state, for example in the detection of image objects or in describing visual scenes, machine learning is already being used effectively in several industries. Cybersecurity, warehouse automation and agriculture are all examples of huge industries where machine learning is being used effectively. In cybersecurity, for example, machine learning is being used to learn what is “normal activity” for today’s enterprises and to alert businesses automatically when anomalies or suspicious threats occur.
Not only can machine learning be used to protect companies from security threats, but it can also be used to detect and mitigate human rights violations. For example, businesses can use machine learning in the supply chain to identify sustainability or modern slavery hot spots in high-risk communities, and work to create solutions. And, where there aren’t solutions, they can rely on sophisticated business networks to identify new suppliers that can meet their sourcing needs, without the ethical setbacks. In healthcare, AI algorithms in medicine can allow doctors to better understand and analyze data, as well as create individualized treatments tailored to a patient’s unique genetic structure.
According to the 2018 Digital & Technology Periscope, AI, along with machine learning and deep learning, is expected to be the top technology that will impact humanity over the next five years. And according to a Pew Research Center Study, nearly one in five Americans indicates he or she knows someone who has lost a job due to automation. This fear, related to a single job and the empathy that comes with job loss, certainly cannot be dismissed. Related to the workforce as a whole, however, it can and should be anticipated that new jobs will be created that will exceed the jobs affected by the reduction. In fact, the World Economic Forum predicts automation will create 58 million new jobs by 2022.
Industry 5.0 is closer than we think. Considering the incredible cost and efficiency benefits to adopting AI, businesses will need to identify all ethical issues that come with using these technologies and provide solutions in advance of implementation, to ensure the benefits do not come at the price of negative societal or economic impact.
As we embark on the next wave of the industrial revolution, businesses need to define how they want to work together with machines, and how the rules of these technologies can be leveraged to achieve desired outcomes. For example, what level of human oversight is necessary when we are trusting decisions to be made based on artificial intelligence, such as by voice-controlled assistants or self-driven cars? The fact that this is also an ethical topic is demonstrated clearly by the fact that vehicles must make decisions in the event of an unavoidable collision. It is the classic trolley problem presented by numerous philosophers – should one person lose his or her life to save the lives of five? And how can we expect a computer to make that decision, when humans have yet to come up with a perfect answer?
While there are controversial issues that coincide with the widespread adoption of this technology, the further development and experimentation of artificial intelligence will lead to promising benefits for companies that – when implemented ethically and cautiously – will overcome the potential drawbacks. To overcome these drawbacks, it is essential to establish a clear framework and rules for the development and use of intelligent technologies. As Andrew Ng, former senior scientist and assistant professor at Stanford University, points out, “Artificial intelligence is the new electricity.” This marks the beginning of Industry 5.0.