6 research has indicated russell and norvig 2019 that

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Research has indicated (Russell and Norvig, 2019) that distributed-ledger technologies have provided trust in an untrusted environment attributed to the ever-evolving digital changes around the globe. Such techniques provide value to businesses and also removes friction by making the ledger independent of individual applications as well as participants. They only enable distributed trust and allow untrusted parties to undertake commercial transactions. Therefore, we can conclude that N are a powerful tool for digital business due to its ability to create trust and also remove business and technology friction (Floridi, et al, 2018). 2.2 Technologies Driving AI AI is driven by several technological advances with the ability to think and learn just like humans. For instance, big data can be transformed into knowledge. A good example is in AlphaGo which was developed by DeepMind as it acquires and develops capabilities which include an intuitive sense[ CITATION Dee19 \l 1033 ] . Moreover, software designed by DeepMind controls a significant amount of variables, but in the end, it tends to improve power efficiency [ CITATION Dee19 \l 1033 ]. Human-machine hybrid- augmented intelligence is another technology driving AI especially when one talks of general information. In this technology hybrid intelligence systems are formed as a result of a cooperation between computers and humans. In the process, augmented intelligence is created. Thus, brings about arguments of whether machine intelligence will ever surpass human knowledge of which studies have proved to be unlikely in the next 60 years (Pan, 2016). 7
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2.3 AI Setbacks The concept of automation, robots and also central nervous system of machines are critical areas of focus in AI research. In a report published in England, a significant setback as far as the development of robots is concerned was that the results of its construction were disappointing since the research did not make any substantial value and this was eventually cancelled (Lighthill, 1973). By cancelling such effects clearly shows how insignificant previous research was in terms of causing wastage regarding resources that were made available to undertake the study. Another setback in AI is the failed development of an intelligent computer in Japan which was expected to create something that can infer and process knowledge (Pan, 2016). Lastly, another setback that occurred during the development of AI was during the attempted manual construction of an encyclopedia of knowledge at Stanford University in 1984 (Poli et al, 2010). However, this did not go as well as the desired results were not achieved due to the amount of data and knowledge that was possessed by the search engines. 2.4 Ethics in AI Ever since the development of AI, there have been fundamental questions concerning its ethical issues as well as economic impact (Cath, et al, 2018). Due to its wide range of applications, AI has permanently become an interesting field of study to the general public. Its exponential increase in data usage has also led to a substantial increase in
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