{"id":4468,"date":"2014-12-07T15:19:05","date_gmt":"2014-12-07T09:49:05","guid":{"rendered":"http:\/\/ucanalytics.com\/blogs\/?p=4468"},"modified":"2017-09-26T20:08:41","modified_gmt":"2017-09-26T14:38:41","slug":"intelligence-artificial-intelligence-collaborative-decision-making-data-science","status":"publish","type":"post","link":"https:\/\/ucanalytics.com\/blogs\/intelligence-artificial-intelligence-collaborative-decision-making-data-science\/","title":{"rendered":"Intelligence and Artificial Intelligence – Collaborative Decision Making with Data Science"},"content":{"rendered":"
\n
\"Collaborative<\/a>

Collaborative\u00a0Decision Making with Data Science – by Roopam<\/p><\/div>\n

Recently in a BBC interview, Stephen Hawking, the eminent theoretical physicist, warned about a possibility of a doomsday scenario because of\u00a0the rise of artificial intelligence. In his words “the development of full artificial intelligence could spell the end of the human race”. This is the same fear the Terminator series of movies have showcased. It is notable that Hawking, because of his medical condition, uses a technology based on artificial intelligence to communicate with the world. In the same interview, he also praised the current artificial intelligence technologies that collaborate with humans to enhance human lives<\/p>\n

In this article, I will evaluate the possibility of a new era where man and machine (artificial intelligence) will work together to improve the decision-making process and human lives. Data science, analytics, and machine learning are at the core of evolution of artificial intelligence. Let’s try to\u00a0understand\u00a0the power of collaborative decision making between intelligence and artificial intelligence\u00a0through the game of chess.<\/p>\n

Chess and\u00a0Decision-Making<\/span><\/h2>\n

Garry Kasparov, the Russian Grandmaster, \u00a0is considered by many to be the greatest chess player of all time. In May 1997 he played a series of six chess games with the IBM supercomputer Deep Blue. Deep Blue defeated Garry Kasparov with a margin of\u00a03\u00bd\u20132\u00bd. Many termed this as the dawn of a new era where\u00a0machines will triumph over humans. However, Garry Kasparov himself saw this as an opportunity and conceived the idea of a new chess tournament called Advanced Chess or cyborg chess. In \u00a0Advanced Chess, a game is played between teams (with humans and computers) rather than individual chess players.\u00a0<\/span>The first game of Advanced Chess was played between the team of Garry Kasparov and computer vs. Veselin Topalov and computer. Kasparov was a far superior player than Topalov and in a human only tournament defeated Topalov with a huge margin of 4-0. However, in this new dynamic of collaboration between humans and computers, Kasparov and\u00a0Topalov\u00a0settled for a tie of 3-3.<\/p>\n

Later in 2005, based on Advanced Chess a new form of a tournament was evolved called Freestyle Tournament. In this, a team can be comprised of any number of humans and computers. That same year what happened surprised everyone. ZackS, a team with\u00a0amateur chess players Steven Cramton (ranked 1685), \u00a0Zackary Stephen (ranked 1398), and their much inferior computer systems defeated teams with Grandmasters and supercomputers.\u00a0This according to me was the new dawn of decision making where intelligence and artificial intelligence\u00a0were working together and collective power was more than its parts.<\/p>\n

Intelligence and Artificial Intelligence<\/span><\/h2>\n

There is a fundamental difference in the way humans think and machines think. Let’s go back to the Garry Kasparov and Deep Blue chess series. Gary Kasparov while playing, consumed about 20 Watts of energy whereas Deep Blue consumed\u00a0many thousand Watts of energy. The reason for this is humans use intuition and years of experience embedded in their neural circuitry to play a game. On the other hand, computers operate on brute force.<\/p>\n

Let me try to create a distinction between intuition and brute force through this story about Carl Gauss, one the greatest mathematicians ever. This story is from the time when Gauss was in his primary school. A lazy mathematics teacher, to kill time, asked the pupils in Gauss’ class to add all the numbers from 1 to 100. All the other students took the brute force route of adding one number at a time. Carl Gauss ,being a genius, saw a pattern in this problem. He noticed that 1+99 = 100, and also 2+98 =100 and so on. Hence he rearranged the numbers in the following order<\/p>\n

100+(1+99)+(2+98)+(3+97)+...+(49+51)+50 = 50\u00d7100+50 = 5050\u00a0<\/span><\/pre>\n
Gauss, to everybody’s surprise, reported his right answer in less than a minute and destroyed his teacher’s leisurely time. \u00a0Coming back to chess, computers painstakingly calculate every move and its probability of winning before making a move. Chess, for instance, has more moves possible than the number of atoms in the universe. To calculate every move and winning probability will take\u00a0forever. In contrast, a Grandmaster\u00a0will never make so many calculations but play the game more on his intuition and experience.<\/p>\n
This right\u00a0collaboration of brute force and intuition was the reason why ZackS, a much inferior team, was able to defeat teams with superior players and computers. Grandmasters and supercomputers were possibly not collaborating as well as ZackS.<\/p>\n
Collaborative Decision Making with Data Science<\/span><\/h2>\n
\"Intelligence<\/a>
Intelligence and Artificial Intelligence – Collaborative Decision Making with Data Science<\/p><\/div>\n
As discussed in the last section, optimal\u00a0decision making will be empowered by collaborative intelligence of humans and machines. This requires humans and machines to work as a team. We all know, great teams are not just set of\u00a0great individuals but requires great collaboration and enhancing\u00a0each other’s strength.<\/p>\n
This is true for every single activity in data science and analytics. As a data scientist, one has to be able to\u00a0classify\u00a0aspects that require brute force and others that require intuition and experience. Additionally, while designing decision support system one has to respect human intuition and judgement, along with the calculation power of machines. This will require data scientists to design systems that promote appropriate human and machine collaborations rather than systems skewed in either direction. Even decision makers need to be aware of this aspect that great decisions are made in collaboration with machines.<\/p>\n
Sign-off Note<\/span><\/h4>\n
Coming back to Stephen Hawking’s doomsday prophesy. Hawking has a point in his warning but what we are missing is\u00a0a bigger message in his prophecy. If we act like Carl Gauss’ lazy teacher and let brute force run wild then be prepared for a bleak future. However, if we collaborate well with artificial intelligence and create an optimal team then there is absolutely nothing to worry about. Hence, data scientists and decision makers please stop being lazy and collaborate well with this new technology. It is the combination of intelligence and artificial intelligence that will create a wonderful planet we all strive for.<\/p>\n","protected":false},"excerpt":{"rendered":"
Recently in a BBC interview, Stephen Hawking, the eminent theoretical physicist, warned about a possibility of a doomsday scenario because of\u00a0the rise of artificial intelligence. In his words “the development of full artificial intelligence could spell the end of the human race”. This is the same fear the Terminator series of movies have showcased. It<\/p>\n
Read More…<\/a><\/p>\n","protected":false},"author":1,"featured_media":4469,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_newsletter_tier_id":0,"jetpack_publicize_message":"","jetpack_is_tweetstorm":false,"jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","enabled":false}}},"categories":[64],"tags":[50,7,6,10],"jetpack_publicize_connections":[],"yoast_head":"\nIntelligence and Artificial Intelligence - Collaborative Decision Making with Data Science – YOU CANalytics |<\/title>\n<meta name=\"description\" content=\"In this article we will discuss collaborative decision making with data science (between Intelligence and Artificial Intelligence) for optimal decisions.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/ucanalytics.com\/blogs\/intelligence-artificial-intelligence-collaborative-decision-making-data-science\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Intelligence and Artificial Intelligence - 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