Artificial Intelligence vs. The Human Element: How will machines impact our future?

What is the purpose of AI?

Artificial intelligence (AI) is making “smart” machines — or using patterns and data to predict and produce the best outcomes, and do things better. On his TED Talk, “How AI can bring on a second Industrial Revolution,” Kevin Kelly, the founder of Wired Magazine, defines AI as “the tendency to make things smarter and smarter,” which he calls, “cognifying — cognification.” His definition highlights an important element of AI, which has to do with increasing efficiency and optimizing current processes by using big data and trends to better inform our decisions.

In one of our social implications guest lectures, Pat Virtue defined AI as the science of making machines that think and act like people. As these definitions make evident, the intended purpose of AI is to make a machine that has the capacity as good or much better than human intelligence, so that it can solve problems more precise and derive better solutions than humans can, and increase our productivity while reducing errors.

What are AI’s effects and its future impact?

AI has created several benefits, which include making our lives simpler by having access to information on-the-go and instantly, such as traffic in your area, restaurant recommendations, and what the weather will be like for the next week. Also, it helps with fraud detection and accomplishing dangerous tasks, such as traveling to space with robots, and exploring unknown territories such as the ocean. Some examples of AI include Google search and GPS maps, personal assistants like Siri and Amazon’s Alexa, and even automated driving machines found in Tesla vehicles, Uber, and Waymo. Some of the harmful effects of AI is that it has begun to replace a lot of jobs, in particularly low-skill jobs that can be automated, or involve a lot of repeated tasks, such as cashiers, welding and soldering in assembly lines, and packaging materials.

Major security concerns of AI are that we will not be able to control the technology that we are building, and that in the long-run machines will have the capacity to develop their own identity. The Future of Life Institute points to two social implications, which are that AI can be developed to do something bad or “devastating,” and the second is that you can use AI to do something better or faster, but that there are trade-offs involved. For example, we can set an AI to accomplish a goal or task that is good, but in order to achieve that, it might have to do a “harmful action,” and since it is not a human it does not have the ability to have empathy or care for others, since its goal is to just complete the task. As a recent McKinsey report on AI reminds us, we should not fear the machine, “As we noted above, however, just because an activity can be automated doesn’t mean that it will be — broader economic factors are at play.”

Here is a very insightful model on the effect of AI and automation on jobs:

What are the Technical Aspects of AI?

Well, AI takes data as an input, analyses that data as a process to optimize the best way of completing a specific task, and outputs the most precise way of doing that task. This is increasingly useful for finding strategies to win games such as Go and chess (Google’s AI beats World Champion), to finding patterns and major trends in data (Supervised vs. Unsupervised Machine Learning), and finding the shortest/fastest path to do something (Waze app and GPS).

In relationship to other innovations, AI is the engine driving the Internet of Things, which connects devices to each other, such as your house’s thermometer to your phone. The way this works is that sensors in home appliances track data and the behavior from your phone, so that one day the sensors will be able to control those devices without the input of a human. Finally, other exciting innovations include creating cognitive buildings, which IBM is currently working on, which use AI and pattern recognition to design buildings that will save energy, and essentially run themselves.

Do you think machines and the power of AI can and will replace all jobs in the future? Why or why not? Comment below! Would love to hear your thoughts and opinions on AI.

Sources:

1. “Automation and Anxiety.” The Economist. The Economist Newspaper, 25 June 2016. Web. 03 Apr. 2017. <http://www.economist.com/news/special-report/21700758-will-smarter-machines-cause-mass-unemployment-automation-and-anxiety>.
2. Lewis-Kraus, Gideon. “The Great A.I. Awakening.” The New York Times. The New York Times, 14 Dec. 2016. Web. 07 Apr. 2017. <https://www.nytimes.com/2016/12/14/magazine/the-great-ai-awakening.html?_r=0>.
3. Michael Chui, James Manyika, and Mehdi Miremadi. “Where Machines Could Replace Humans — and Where They Can’t (yet).” McKinsey & Company. July 2016. Web. 07 Apr. 2017. <http://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/where-machines-could-replace-humans-and-where-they-cant-yetLinks to an external site./>
4. Russell, Jon. “Google AI Beats Go World Champion Again to Complete Historic 4–1 Series victory.” TechCrunch. TechCrunch, 15 Mar. 2016. Web. 07 Apr. 2017. <https://techcrunch.com/2016/03/15/google-ai-beats-go-world-champion-again-to-complete-historic-4-1-series-victory/>.
5. Tegmark, Max. “Benefits & Risks of Artificial Intelligence.” Future of Life Institute. Web. 07 Apr. 2017. <https://futureoflife.org/background/benefits-risks-of-artificial-intelligence/>.
6. Wladawsky-Berger, Irving. “Artificial Intelligence’s Long-Term Impact on Jobs: Some Lessons From History.” The Wall Street Journal. Dow Jones & Company, 01 Aug. 2016. Web. 07 Apr. 2017. <http://blogs.wsj.com/cio/2016/07/29/ais-long-term-impact-on-jobs-some-lessons-from-history/>
7. “Energy And Environment.” IBM — Cognitive Buildings — IBM Energy & Environment. N.d. Web. 07 Apr. 2017. <https://www.ibm.com/ibm/green/smarter_buildings.html>.