Currently and in the future, Artificial Intelligence (A.I.) is expected to affect the way we get the news, the ads we received, the things we buy, our transportation system, the jobs we have or may not have any more, our education system, our appliances, and our health. While many of these things are great news, however, we may have to be aware and ready for a rapidly changing world and job security.

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Our news media rely heavily on a social network to distribute the news and also rely on automation of trends, market derivatives, algorithms, analytics to decide which news are presented in the network prime time hours. While we have always relied on data to make decisions, what if these data are manipulated or corrupted using pesky algorithms. Which was the case during the last U.S. election. Many data were manipulated using fake news websites and pesky algorithms. As this news with shocking headlines started to trend on social media, this disinformation would be picked for its popular response and end up on the major news network, and it would take these news network days before correcting them. As a result, studies showed that many voters were influenced or suppressed by fake news. Another trend of Artificial Intelligence is how advertisement is delivered to individuals using personal information collected by the browsers that you used and email accounts.

All the information or communications that you send or share using social media are collected to create smart ads. Eventually, all ads that anyone will see online on T.V. will be tied to their purchase and web activities. These ads will know the clothes that we want to buy and predict the trips or vacations that we want to take or direct us to our weekend activities.  These data used by smart ads are considered as predictors and are used in rudiment machine intelligence that can distribute contents online. On social media it can be the suggested friends, pages, news and other info; in the market, visual advertisement will showcase the foods that they think we want to buy and where they are located, GPS already pre-program your daily trips of the places we usually go or will want to go, the streets we drive on to go to work and school, or anywhere else.

Basically, what we human have been seeking are automations in our lives to make things easier, and once you tie these automations with machine who can do the actual work, that is even better. The first automations in our lives are currently seeing on the internet in the form of research results of our search engine, the GPS mapping, the algorithm results of our newsfeed or trends report. However, these automations will evolve into A.I. Through information gathering, how far are we in that evolution? How it had affected or will affect our jobs in healthcare industry, education, transportation, service industry and auto-industry based on data reviewed through multiple interviews by experts in this matter, university reports and other documents and articles. Some have a doom’s day prediction, and others believe there are the way to prevent a total takeover of A.I. in our lives, while others believe that it will be for the best. For example, according to a PWC study, 38% of U.S. jobs could be lost to automation in the next 15 years. However, the first solution is to know that A.I. is already there and we will get stronger going forward. The first step is to know which jobs will be affected by it and how. In addition, if you just look at what projects major companies are currently working on right now, we can have a clear picture of what jobs will be directly affected incrementally or immediately. These projects are: self-driving truck (Mercedes), self-driving cabs (Uber, Lyft). Ordering kiosk currently in use in some companies (Mc Donald, Burger King), robot servers (McDonald), Ordering and transaction cart (Publix, Walmart), mail delivery drones (Amazon), self-driving planes, drones (Boeing, Lockheed Marten), Automatic Teller system (Citibank, Bank of America, CHASE), Automated 3D Printers, Rudimentary Machine Intelligence (Facebook, Google), Deep Mind (Facebook, IBM, Google). These are just a few developments in the technological pipeline that would eventually make some current jobs more effective or obsolete; Our goals is to find out how.

Transportation

Artificial Intelligence projects that will impact our transportation system in the future are many: self-driving cars, self-driving trucks, GPS control system, and deepmind. One of the most advanced projects is the alliance of Mercedes with Udacity using their advanced A.I. software name nanoDegrees to create a self-driving truck. Udacity has also teamed up with Uber to come up with a self-driving taxi. Both projects are currently on trial stage. Upon full automation or development, these projects might affect 3.4 million jobs. The main purpose for these projects is the avoidance of human errors like truck drivers sleeping during a long trip and they expect the self-driving cars to be more effective on time and delivery. So far, all test show that they might need a driving monitor, especially in the truck trials (S1).  According to the U.S. Bureau of Labor Statistics, the jobs at risk are 2.4 million truck and delivery drivers, 180,000 taxi drivers, 160,000 Uber drivers, 500,000 school bus drivers, and 160,000 transit bus drivers. For this technology to function well it will need the assistance of other AI technology like the GPS, Deepmind, Robotic features, and Cognitive analysis. Currently, a car can self-park, summon, and stay on auto drive. The problems to resolve are test-driving car accident due to missing yellow light, resolving issues with aggressive drivers (S 7, 8). Other projects by other companies that are also in the trial stage:

1. Self-driving cars Google (S 1,8) (Google car has driven on its own for 1,5 million miles, only 300 thousand miles were without an accident)
2. Self-driving cars Apple (S 1,8)(no data)
3. Self-driving cars Tesla (S 1,8) (no data)

The predictions and case study published by the White House in 2016 and conducted by the Council Economic Adviser (CEA) estimated that 2.2 to 3.1 million current part- and full-time U.S. jobs may be endangered or greatly changed by Automated Vehicle technology. Essentially, CEA also confirmed that this does not calculate the types of new jobs that may be created—but rather a calculation of existing jobs that are likely to be affected by AI-enabled AV technology. A second warning is that this technology may take years or decades to happen because there will be a delay especially for safety requirements between technological possibility and widespread adoption. There will also be a delay of adaptation or acceptance by the public.

However, as reported in the journal Artificial Intelligence, Employment and Income by Nils J. Nilsson, new infrastructures will also be needed in order to accommodate these transformative changes in the transportation industry, which in turn will result in creating new jobs.

Automobile Industry

There are two A.I. technologies who have already affected the auto industry, robotic technology, and 3D printing. From the first robot used by GM in 60’s, 70,000 robots are currently in use in the United States. Auto manufacturing jobs have gone from 1.1 million to 532,000 (S 13, 8). Another technology affecting the auto industry is 3D printing that is currently in use to print auto parts (S 14, 8), however, it is projected that by combining robotic technology with 3D printing the auto industry will be again completely transformed as far as the labor force is concerned.

Construction Industry

Another industry that is affected greatly by 3D printing is construction. Companies all over the world are already showcasing their construction work using 3D printing. Each company has developed its own technology: from WATG who used carbon fibers and plastic to construct a freeform structure, CO2NCRETE who collects carbon dioxide from the air and turn it into concrete print stock, and Emerging Object who 3D print bricks. These technologies are already in use. It is estimated that 12 million will be affected by these new technologies, jobs such as welder, masons, and construction materials shop and warehouses (S 15,8).

Healthcare

Healthcare workers will have many AI technologies in their crosshair either as tools or as replacement workers: 3D Printing/ bio-printing that are currently in use, robotic assistant currently in use, and deepmind already in use by many hospitals around the World.  36,000,000 can be affected by these new advancements.

3D printed implants and prosthetics are already in use and can be printed at the recovery center. It is not clear what jobs will be affected except the manufacturing companies who used to build these prosthetics and implants. However, manufacturing jobs will be created to build these printers. Bioprinting is currently under development and will be able to print organs for transplants on the spot at the clinic or hospitals.

Medical and pharmaceutical companies are using robotic technology as a mean for drug delivery, and operation. Robotics already created and sold robotic that can assist a doctor in operation rooms. Johnson and Johnson’s Sedasys system received FDA approval to provide anesthesia for standard procedures like colonoscopies. A doctor managing multiple machines at once can reduce the medical cost instead of having a dedicated human anesthesiologist. Many robots are in various stages of testing and approval for diagnosing disease. For example, IBM’s Watson demonstrated a higher rate of accuracy for diagnoses than human doctors.

When it comes to services all technologies are welcomed: Internet of Things (IOT) already in use, deepmind in use, algorithm, smart ads are been utilized by retail companies, finance and banking services. This industry employs more individuals than any other industry, 126,000,000 as of March 2017.  As a result, all tech companies that are involved in an A.I projects, Google, Facebook, IBM, Microsoft are very much vested in DeepMind and already in use. Currently, most phone calls inquiries made to any major companies are handled by artificial intelligence or automatic phone response system that is becoming more efficient by using voice responses instead of key responses. DigitalGenius, for example, has created an automated customer service which enables companies to automate basic questions and answers, and even chats with customers by harnessing natural language processing and machine learning to create reactions. Robots can now impersonate human speech patterns to provide service that is fast and easy to consumers, and very inexpensively for companies.

From Finance to shopping, the service industry is experiencing a rapidly increasing amount of data. Some financial services companies are turning to artificial intelligence to keep up with demand. Robots are using predictive systems and market data to forecast stock trends and manage finances. Financial advice is becoming automated, with a growing trend towards “roboadvisers”” that automatically dispense advice and suggestions to financial clients, especially those with relatively simple financial problems. Robots is using a variety of algorithms to provide recommendations that best meet clients’ spending, saving, and investment habits. Altogether, 174 million jobs have been or will be affected by A.I. technologies. That is more than half of the U.S. population.

Chart Analysis

Other projected data about the labor force were presented as charts by PWC, and outcome tables by the Executive Report by the White House in 2016. For example, the flip that will eventually occur from higher numbers having more workers at the high-value function than the low-value functions as it is now.

The reason for this shift as shown in the second graphic by PWC, the labor tasks as A.I. evolves from assisted intelligence, that is now, to augmented intelligence, then to autonomous intelligence.

The Executive reports provided by the White House and charts created by BLS, CEA, and PAAC seem to agree with the PWC forecast that highly educated or skills workers and high paying jobs will be the less vulnerable, and lowly educated workers and the least paying jobs will be the most vulnerable:

Based on these charts provided by the Bureau of Labor Statistic, the less money a worker earns per hour, the higher the probability that their job will be replaced by automation. Similar effect will be felt by workers who have less than a high school diploma than a worker with a higher degree. However, the executive report proposed that the A.I. development and implementation be done incrementally to avoid irreversible negative impact to the labor market (S 6, 7, 8).

In conclusion, I believe that A.I., in general, should be part of every government local or national consolidated planning for the future that they put out every five to ten years. They cannot be caught off guard by new business models using A.I., and the private companies may have to also play a role in collaborating with these local businesses, national and local governments before launching projects that may have big economic impacts. Because we will not want in the future, Uber drivers attacking autonomous Uber vehicles.

Sources

1. Nils J. Nilsson (Summer 1984) Artificial Intelligence Center SRI International Menlo Park, California 94025. ” Artificial Intelligence, Employment and Income (http://ai.stanford.edu/~nilsson/OnlinePubs-Nils/General%20Essays/AIMag05-02-002.pdf )
2. Report of the 2015 study panel ( September 2016) Stanford University” artificial intelligence and life in 2030 one hundred year study on artificial intelligence | (https://ai100.stanford.edu/2016-report)
3. MICHAEL MILLS (November 3, 2015). What is artificial Intelligence (“AI”)? What is AI doing in law? Who is doing it? And where is it headed?” Artificial intelligence in law – the state of play in 2015?(https://www.legaltechnology.com/latest-news/artificial-intelligence-in-law-the-state-of-play-in-2015/)
4. PWC A.I. Report (2017). This original research unpacks key ways AI may impact our world, delving into its implications for society, service, and management. (https://www.pwc.com/gx/en/issues/data-and-analytics/publications/artificial-intelligence-study.html)
5. Cornell University A.I. Project Pipeline (2017) (http://www.cs.cornell.edu/courses/cs478/2001sp/mllinks/interesting_ai_demos_and_project.htm)
6. Jason Furman John P. Holdren Chair, Council of Economic Advisers Director, Office of Science and Technology Policy, Cecilia Muñoz Megan Smith, Director, Domestic Policy Council U.S. Chief Technology Officer, Jeffrey Zients, Director, National Economic Council (2016). Artificial Intelligence Automation and the Economy, Executive Office of the President. (https://www.gpo.gov/fdsys/pkg/DCPD-2015CHECKLIST/pdf/DCPD-2015CHECKLIST.pdf)
7. Cromwell Schubarth (Sep 13, 2016, Updated Sep 13, 2016) Silicon Valley Business Journal, “Udacity teams with Mercedes, others, to train selfdriving cars tech engineers” (https://www.bizjournals.com/sanjose/blog/techflash/2016/09/udacity-teams-with-mercedes-others-to-train-self.html)
8. Bureau of Labor Statistic all labor data (bls.gov)
9. Multiple Writer (July 1915–July 2015). The Monthly Labor Review through a century of economic transformation (https://www.bls.gov/opub/mlr/2016/article/pdf/the-monthly-laborreview-through-a-century-of-economic-pdf)
10. James Brown (2012). The future of the economy is in STEM,” “Intro to tomorrow’s jobs” (https://www.bls.gov/careeroutlook/2014/spring/art01.pdf)
11. Google DeepMind: What is it, how does it work and should you be scared? (http://www.techworld.com/personal–tech/google–deepmind–what–is–ithow–it–works–should–you–be–scared–3615354/)
12. Carl Benedikt Frey and Michael A. Osborne ( September 17, 2013) THE FUTURE OF EMPLOYMENT: HOW SUSCEPTIBLE ARE JOBS TO COMPUTERISATION? (http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_ of_Employment.pdf)
13. Tom Ahlborn (2011). Industrial Robotics in the Automotive Industry https://www.bastiansolutions.com/blog/index.php/2015/09/17/industri al–robotics–automotive–industry/#.WRINukXyvcs
14. Multiple authors (2017).  What is 3D printing? https://3dprinting.com/what–is–3d–printing/
15. Nick Hall (2016. Top 10 3D printed construction innovations https://3dprintingindustry.com/news/top–10–3d–printed–constructioninnovations–83578/

References

1. Chan Connie (2017). 5 Industries Being Most Affected By Artificial Intelligence. https://www.fowcommunity.com/blog/future–work/5industries–being–most–affected–artificial–intelligence
2. Anna Sekaran (2016) IBM Media Relations. Industry Leaders Establish Partnership on AI Best Practices.  https://www–03.ibm.com/press/us/en/pressrelease/50668.wss
3. John Ward (2012) International Trade Administration Journal. THE SERVICES         SECTOR:  HOW BEST TO MEASURE IT? http://trade.gov/publications/ita–newsletter/1010/services–sector–howbest–to–measure–it.asp
4. Elizabeth Weise (2016). USA Today. Amazon just opened a grocery store without a checkout line. https://www.usatoday.com/story/tech/news/2016/12/05/amazon–gosupermarket–no–checkout–no–cashiers–artificial–intelligencesensors/94991612/ (not reviewed, not journal)
5. AUTONOMOUS VEHICLES | SELF-DRIVING VEHICLES ENACTED LEGISLATION   (2017). http://www.ncsl.org/research/transportation/autonomous-vehicles-selfdriving-vehicles-enacted-legislation.aspx

by Schiller Ambroise

AN experienced professional with a demonstrated history of working in the non-profit industry. Skilled in Nonprofit Organizations’ capacity building, Entrepreneurship, Event Management, Public Speaking, Resources Development, and Marketing. Strong community and social services experiences with continuing studies in Criminal Justice/Law focused in Social Justice and crimes, International Law, Business Management, and Cyber Security from St. Thomas University.

Schiller Ambroise

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