Page 226 - Ai_417_V3.0_C9_Flipbook
P. 226

Job Loss

              With more machines being used for day-to-day work, the fear of unemployment is increasing. With the emergence
              of AI and automation, there will be technology-driven societal changes. The study reveals, depending upon various
              adoption scenarios, automation will displace between 400 to 500 million jobs by 2030. There will be shifts in job
              categories that will impact the economies of many developing countries. AI robots were replaced with human

              employees in a Japanese Henn-na Hotel. This hotel started with hospitality robot staff in all the departments,
              but with time the robots could not provide efficient services to its customers and were replaced with human
              employees after much struggle.


              Personal Privacy
              In today’s scenarios, we are surrounded by technology where an individual's personal life can be tracked easily. The

              gadgets and the apps used on a daily basis are AI-enabled. The data gathering abilities of AI can access your data
              from the social networking websites used by you. The cameras installed use facial recognition to identify you in the
              crowd. You are being followed and recorded everywhere without information. Apple’s iPhone X used an advanced
              front-facing camera and machine learning to create a 3-dimensional map of a face for Face Id recognition. The
              company claimed that it is programmed to work without errors even for cosmetic changes. But within a few days
              of its launch, a Vietnam-based security firm-Bkav could unlock the Face ID using 3D-printed masks.


              What if AI Makes Mistakes

              Yes, it's true, AI can make mistakes. It's recorded that in 2016, when the Uber company conducted a test on self-
              driving cars in San Francisco, Uber’s autonomous vehicle ran six red lights. The situation got out of hand, but a
              licenced driver was made to sit behind the wheel in case of emergency so he took over control of the situation
              immediately. In another situation in the same year, Microsoft’s chatbot, Tay was released on Twitter. It is based
              on machine learning, natural language processing and social networks. It learnt its language from the people on
              Twitter over time that enabled it to have a meaningful conversation based on a topic. But sadly, it was taken offline
              within 16 hours of its launch as it started tweeting randomly some abusive and offensive content.


              Autonomous Weapons

              They are also known as killer robots. They can aim independently by pre-programmed instructions. Most of the
              technically advanced countries are developing these autonomous weapons to safeguard themselves. There are
              many dangers in using these weapons.


              Black Box Problem

              This problem is more associated with the neural networking of AI than simple machine learning algorithms. The
              system uses a huge data bank to learn and produce results. There is no way to understand how the system is
              working, what exactly the algorithm is doing and what method it is using during the process. Since there is no
              insight, it is called a Black Box problem. This happens because the data that the AI system is working on, goes
              through a lot of neural nodes which mutates it, making it extremely difficult to determine the working and the
              source of the problem.






                    224     Touchpad Artificial Intelligence (Ver. 3.0)-IX
   221   222   223   224   225   226   227   228   229   230   231