Artificial Intelligence

WHAT IS ARTIFICIAL INTELLIGENCE? 

The term “artificial intelligence” is loosely used to describe the ability of a machine to mimic human behavior. AI includes well-known applications, such as Siri, GPS, Spotify, self-driving vehicles and the larger-than-life robots made by Boston Robotics that perform incredible feats.

In simple words, (AI) refers to use of robots and computer systems to make decision of expert nature and solve unstructured problems in an efficient way.

EXAMPLES OF (AI)?

1.     China is using facial recognition to closely scrutinize its citizens who could be punished for certain transgressions. The country has been accused of using facial recognition to profile Muslims in its Xinjiang region. Recently, there were privacy concerns raised about face app, the Russian-backed, face-ageing application. 

2.     In an effort to save billions of dollars in labor costs,   Amazon warehouses have thousands of little, cute, orange robots made by Kiva, a robotics company acquired by Amazon for $775 million. The Kiva robots needs only 15 minutes to find, pick and package an order, whereas a human needs about 60-75 minutes to accomplish the same tasks. 

  

3.    Many large banks and  financial institutions are beginning to digitize parts of their business processes to prepare for future initiatives in automation and machine learning. This is particularly true with loan processing. These functions could become faster and more accurate if they use digitized data that is more easily accessible than paper document. For instance, use of expert system help bank to   hire employee with little experience with the responsibility to only put queries into the system asked by customers. Expert system or (AI) would then solve the queries in a much better way than manager of a bank is capable of.

4.    Companies such as Waymo  and Tesla are heavily invested in driver less cars. Currently, Waymo has begun testing of driver less cars again after stopping in 2017. Testing is done with drivers inside the vehicles until the company is able to gain enough data to move towards a completely driver less solution.

THREATS POSED BY (AI)? 

1.               Political, legal, and social ramifications: As Bostrom advises, rather than avoid pursuing AI innovation, "Our focus should be on putting ourselves in the best possible position so that when all the pieces fall into place, we've done our homework. We've developed scalable AI control methods, we've thought hard about the ethics and the governments, etc. And then proceed further and then hopefully have an extremely good outcome from that." If our governments and business institutions don't spend time now formulating rules, regulations, and responsibilities, there could be significant negative ramifications as AI continues to mature. 

2.   In China and other countries, the police and government are invading public privacy by using face recognition technology.

3.   AI technology makes it very easy to create "fake" videos of real people. These can be used without an individual's permission to spread fake news, create porn in a person's likeness who actually isn't acting in it, and more to not only damage an individual's reputation but livelihood. The technology is getting so good the possibility for people to be duped by it is high.

ADVERSE IMPACT ON JOBS?

1.     A two-year study from McKinsey Global Institute suggests that by 2030, automation will displace between 400 and 800 million jobs by 2030, requiring as many as 375 million people to switch job categories entirely.

   

2.    Jobs performed by people with a 4-year university degree, which were once largely immune from automation, could be the hardest hit. These include market research analysts, sales managers, programmers, management analysts, and engineers. Positions that are “heavily involved in pattern-oriented or predictive work” are expected to be “especially susceptible to the data-driven inroads of AI,” according to the analysis.

3. Radiology and taxi driving — two jobs transformed by technology. Computers are starting to read medical images just as well as radiologists. But radiologists add value in other ways machines can’t: by communicating with patients and integrating medical information into diagnoses and treatment plans. This leaves radiologists with a skilled portion of work that cannot be automated, giving them a better shot at keeping their exclusive high-paying jobs.

4.        On the other hand, we have the taxi driver whose job consists of two basic parts: navigating and driving. Years ago, taxi drivers had to study and memorize entire city maps, a specialized skill that allowed only the qualified few to make money. With the advent of GPS and smartphone apps, the navigation aspect has gone digital, allowing more people to become drivers, and in turn, drive down wages. Contrast that with the other piece of their job — pushing the gas pedal, hitting the brakes and turning the wheel — which doesn’t take much expertise.

5.   Blue-collar and white-collar jobs will be eliminated—basically, anything that requires middle-skills (meaning that it requires some training, but not much).

6.  While the first robots in the workplace were mainly involved with automating manual tasks such as manufacturing and production lines, today's software-based robots will take on the repetitive but necessary work that we carry out on computers. Filling in forms, generating reports and diagrams and producing documentation and instructions are all tasks that can be automated by machines that watch what we do and learn to do it for us in a quicker and more streamlined manner. 

7.         AI-enabled terrorism: Artificial intelligence will change the way conflicts are fought from autonomous drones, robotic swarms, and remote and nanorobot attacks. In addition to being concerned with a nuclear arms race, we'll need to monitor the global autonomous weapons race.

   

        

The Skills You Need to Work in Artificial Intelligence?

1.               Researchers use their breadth of knowledge in theory and study to reveal new types of systems and capabilities. Researchers hypothesize new or different ways for machines to think and test their research for real-world feasibility. 

2.             Algorithm developers take AI research and transform that research into repeatable processes through mathematical formulas that can be implemented using hardware and software.

3.        Software developers and computer scientists use those algorithms to write sophisticated pieces of software that analyze, interpret and make decisions.   

4.     Hardware technicians build pieces of equipment (like robots) to interact with the world. Robots use its internal software to move and operate. 

5.       Math: statistics, probability, predictions, calculus, algebra, Bayesian algorithms and logic

6.  Science: physics, mechanics, cognitive learning theory, language processing

7.       Computer science: data structures, programming, logic and efficiency

Non-Tech Skills for Artificial Intelligence

8.    Critical thinkers: They take nothing at face value and are naturally curious. They believe in trial and error and must test and experiment before making a concrete decision. 

9.   Like to push the envelope: (AI) is all about pushing the boundaries. Pegging the capabilities of hardware and software to their max, always looking for more. More ways to improve existing systems. More ideas for inventing new ways to live. 

10. Live naturally-curious lives: Always wanting to know more, artificial intelligence pros want to know how things work. They don’t just look. They observe. They don’t hear. They listen. 

11.        Don’t get easily overwhelmed: They understand that artificial intelligence is highly technical, but also realize that venturing into uncharted waters is difficult and mysterious. They enjoy the process rather than getting frustrated by it.

12.     Communication skills: Ability to communicate clearly and effectively is something that helps us to face the challenges imposed by (AI).

13.     Emotional intelligence: (AI) is not capable of understanding the feelings of others. This is something that we can learn and develop to have edge on (AI).

14.     Interpersonal skills: Able to understand verbal and non-verbal messages is a significant   to maintain relationships.

15.  More and more of us will get used to the idea of working alongside AI-powered tools and bots in our day-to-day working lives. Increasingly, tools will be built that allow us to make the most of our human skills – those which AI can't quite manage yet – such as imaginative, design, strategy, and communication skills.

16. The rollout of 5G and other super-fast wireless communications technology will bring huge opportunities for businesses to provide services in new and innovative ways, but they will also potentially open us up to more sophisticated cyber-attacks. Spending on cyber security will continue to increase, and those with relevant skills will be highly sought-after.

17. Low- and high-skilled jobs have so far been less vulnerable to automation. The low-skilled jobs categories that are considered to have the best prospects over the next decade — including food service, janitorial work, gardening, home health, hairdresser, childcare, and security — are generally physical jobs, and require face-to-face interaction. At some point robots will be able to fulfill these roles, but there’s little incentive to roboticize these tasks at the moment, as there’s a large supply of humans who are willing to do them for low wages.

CONCLUSION

Looking back on history, it seems reasonable to conclude that fears and concerns regarding AI and automation are understandable but ultimately unwarranted. Technological change may eliminate specific jobs, but it has always created more in the process.

To prevent ourselves and our future generation to become the victim of (AI), we must focus on improving our education system that not only focuses on theoretical learning but also on practical learning. We should also accept that learning doesn’t end with formal schooling. The exponential acceleration of digital transformation means that learning must be a lifelong pursuit, constantly re-skilling to meet an ever-changing world.

Making huge changes to our education system, providing means for people to re-skill, and encouraging lifelong learning can help mitigate the pain of the transition, but is that enough?

There are other factors that determine whether a human or machine will be hired for the job. One is relative cost, meaning how much the boss has to pay a human versus a machine to get the work done. Even if a robot can feasibly do a task, it still has to make economic sense to install and use it. Another is social acceptability — whether society is willing to automate a job. For example, it may be a long time before we are comfortable with robo-judges, robo-legislators or robo-priests. Maybe. Maybe not.