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The United States, for now, has the lead in AI development when it comes to hardware, research & development, and has the most dynamic commercial AI sector. Companies like Uber and Lyft use the technology to predict rider demand, while Amazon, Facebook, and Wells Fargo all use AI and Machine Learning for facial recognition, fraud prevention and to better understand customer habits.
But what is the future of AI? Let’s examine our top 5 predictions of how artificial intelligence will be applied in the future.
Artificial Intelligence (AI) technology is looking to transform everyday life from the way we currently see it. As an example, the machine learning technology could potentially revolutionize Human Resources responsibilities like recruiting, performance evaluation and education to name a few. AI has the ability to streamline the human resources process by relying more on the analytical processing of big data instead of individual observations that usually take up time and resources. From a recruiting perspective AI software can design interview questions for potential hires that focus on the person’s professional competency for a particular job without ever knowing a person’s race, gender or ethnicity. This technology could also benefit the resume filtering process, which can be a very time-consuming process.
An immediate effect that Machine Learning can have from an international business standpoint is its effect on language barriers. There are over 6,500 spoken languages in the world, and many of the more obscure languages are spoken by demographics who are isolated from the global economy. Removing language barriers through technology connects more communities to global marketplaces. China recently has expressed high interest in machine learning. Their government has set a goal of spending $150 billion dollars to achieve global leadership when it comes to technology by 2030. China has more access to data than any other country due to its population. That data will enhance their machine learning capabilities which will, in turn, make better predictions, better efficiency, higher profits, less labor, less cost and so on.
Data and analytics have been changing the basis of competition for years. Businesses are using information to enhance their core operations as well as create new business platforms within the companies themselves. However, businesses are only able to obtain and analyze a fraction of the info that would help them with revenue and profit gains. One way for businesses to obtain that additional valuable information is via Machine Learning, which will help large businesses to remain successful and relevant within their industry.
Though it is now one of the most talked about and controversial topics in modern science, few truly understand the implications of autonomous vehicles. Traffic accidents are one of the most significant causes of permanent disability in the United States and are on track to being in the top 5 causes of death worldwide. Currently, an average of 102 people in the United States die in traffic-related accidents every day. Additionally, billions of dollars are being wasted annually on gasoline expended by cars that are stationary in traffic. Autonomous vehicles have been regarded as a likely solution to the problems of driver safety, fuel economy, and traffic reduction; they are also expected to increase quality of life for the elderly and those with visual impairments. Though statements made by certain corporate moguls promising the commercial release of autonomous vehicles in the near future have been met with derision and contempt, the rate of development of artificial intelligence, specifically of specialized algorithms for autonomous driving, suggests that such promises could indeed be realized in the next five to ten years. If so, the effects that democratized autonomous vehicles will likely have on driver and pedestrian safety, the global economy, the environment, and quality of life are astounding.
In the future, as AI gets smarter, we’re going to have to establish better tools to enable us to understand why AI systems make their decisions and what levels of risk different algorithms can deal with when making those decisions. With an ability to have a “conversation” with an AI about its actions, we’ll be able to feel safer giving it the authority to make risk-sensitive decisions that impact our lives, ranging from management of local public transportation infrastructure, to controlling the production of currency by the Federal Reserve without human intervention. Similar to how we certify industrial equipment and smog test vehicles, government authorities will have to be established to develop certification programs for algorithms, verifying that machines learn accurate representations of the world and have low probabilities of being fooled into making mistakes that could have devastating effects on humanity.
The rate at which artificial intelligence and machine learning are advancing makes predicting their impact on even the near future all but impossible. Even so, their potential benefits in the fields of autonomous driving, physics and neuroscience could very well define a new chapter of human existence, a chapter in which humans will travel safer, know more about the universe, and transcend physical disabilities and limitations. No matter how fantastical an application of AI might seem, its realization is always closer than it may appear.
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