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  1. 1. Balancing Human Creativity with Algorithms Marshall Sponder Lecturer, Zicklin School of Business & Associate Professor, Rutgers Business School Global Artificial Intelligence Conference
  2. 2. What is covered in this presentation? 1. Introduction 2. Darker Side of Algorithms 3. Algorithms and Creativity 4. Textbook & Summary
  3. 3. Introduction
  4. 4. Here today to speak about a way of humanizing Big Data and Algorithms Marshall Sponder develops and teaches online and hybrid courses at Zicklin School of Business and Rutgers University where he holds a dual appointment. At Zicklin, he teaches Web Analytics courses while at Rutgers he teaches an online class called Social Media for the Arts. Marshall is the author of Social Media Analytics (McGraw-Hill 2011) and Digital Analytics for Marketing (Routledge, 2017). Marshall is a Board Member Emeritus at the Web Analytics Association, now called the DAA.
  5. 5. The Digital Marketing Major is part of the success story of Baruch
  6. 6. Digital Marketing CORE courses and some ELECTIVES at Zicklin School of Business
  7. 7. Social Media for the Arts is an Online, Asynchronous learning course I author and teach at Rutgers University this semester there is 1436 students and is growing exponentially every year.
  8. 8. Lets start with the Darker Side of Algorithms
  9. 9. Uber Surge Pricing generated A $1,100 Bill For an Hour-Long Ride To this day no one understands what is actually going on inside the Uber Surge Algorithm, though several experts have an approximate idea of how it works.
  10. 10. Instagram uses I will rape you threat as a Facebook ad due to a Facebook algorithm The trouble is Facebooks business model is structurally identical whether advertisers are selling shoes, politics or fake diet pills, and whether theyre going after new moms, dog lovers or neo-Nazis. The algorithms dont know the difference, and Facebooks customers are not its users.
  11. 11. Algorithms can be as biased as their trainers. Google is more likely to advertise executive-level salaried positions in the UK to search engine users if it thinks the user is male, according to a Carnegie Mellon study. Photograph: Yui Mok/PA m/technology/2016/aug/03 /algorithm-racist-human- employers-work#img-2
  12. 12. An algorithm that automatically delivers a dont interview verdict to candidates with criminal records disproportionately impacts black job seekers. thm-racist-human-employers-work#img-2
  13. 13. One of the challenges in algorithm-based hiring is that currently there is no standard way to measure the outcome of an algorithms choices. thm-racist-human-employers-work#img-2
  14. 14. But it is Important to get algorithms right as they are running everything now - Many prison inmates' futures depend on racially biased algorithms
  15. 15. There is Hope: scientists have devised a way to test whether an algorithm is introducing gender or racial biases into decision-making. https://www.theguardian.c om/technology/2016/dec/ 19/discrimination-by- algorithm-scientists-devise- test-to-detect-ai-bias
  16. 16. Police use a Geo-tracking Algorithmic Surveillance Tool, Geofeedia, to Scan Social Media for criminal activity.
  17. 17. Algorithms are best viewed in terms of expected inputs vs. expected outputs, especially when the programming code can not be examined. Outputs that are several standard deviation above or below the mean or average (such as a 1000.00 cab ride that normally costs 100.00) would be a red flag that there is something wrong or abnormal about what the program (algorithm) is doing. Even without programming knowledge, anyone can begin to examine algorithms in this way.
  18. 18. Watch how you handle big data, FTC warns businesses - 'We need systems for auditing the proprietary algorithms,' an ACLU attorney says
  19. 19. How to balance Algorithms with human creativity and keep the best of both!
  20. 20. Understanding Algorithms Algorithms are a series of instructions that are used to find patterns within a set of data and make decisions upon that data. Computer and humans run algorithms. Many of the algorithms run on computers are a black box and can not be examined closely.
  21. 21. In Music Algorithms are beginning to choose the next hit songs, and perhaps, predetermine them. A Machine Successfully Predicted the Hit Dance Songs of 2015 Each song is encoded into various measurements that can be operated on by specific algorithms and plotted, as show in the chart on this slide. The algorithm makes a prediction of the likelihood a song will be a Hit based on its position on the cartesian graph, and its calculated score.
  22. 22. A Machine Successfully Predicted probabilities connected with Hit Dance Songs of 2015, and is probably selecting even more hits in 2018 machine-successfully-predicted-the-hit-dance-songs-of-2015
  23. 23. The Washington Posts robot reporter has published 850 articles in the past year like this one
  24. 24. Creating Computer Vision and Machine Learning Algorithms That Can Analyze Works of Art at Rutgers University.
  25. 25. The creativity algorithms were tested on two data sets containing more than 62,000 paintings. The algorithm gave high scores to several works recognized by art historians as both novel and influential, including some of the works shown in Figure 3. Ranking even higher than Pablo Picassos Young Ladies of Avignon (1907) in the same period were several paintings by Kazimir Malevich. This result initially surprised me, as I knew little about Malevichs work. The implications suggest that the art market, including historical art, may be over-rated for some artists, and under valued, for others.
  26. 26. Exploring world- wide clothing styles from millions of photos @ Cornell University
  27. 27.
  28. 28. Amazing New Algorithms Will Fix Your Photos Before You Even Take Them
  29. 29. Googles Algorithmic Photographers Are Almost as Good as the Real Deal googles-algorithmic-photographers- are-a/
  30. 30. New algorithm gives photos Picasso-style makeovers
  31. 31. This Apps' Creations Sure Look Like Masterworks, But Is It Art?
  32. 32. Algorithms can turn sketches into art with machine learning (Vincent AI)
  33. 33. Search Engines such as Bing have Automated Image Detection In Visual Search Queries searchers can also use semantic search keywords (supplied) to dig deeper and find images with specific elements in it.
  34. 34. Impressive Adobe Algorithm Transfers One Photos Style Onto Another
  35. 35. Google releases smart image analysis tools to let robots recognize images, text
  36. 36. Google has a Cloud Vision API (several others have similar offerings) that is easy to build applications around. I put the building I just moved into, based on a photo I took recently, and the Google Cloud Vision API did a pretty good job of decoding its meaning.
  37. 37. Text Analytics platforms have been successfully employed, piggybacking off algorithms to detect emotions in text (and images), then isolate it image taken from a Crimson Hexagon analysis.
  38. 38. Algorithms can detect the most interesting parts of an image and how memorable it is.
  39. 39. Geodata can be easily surfaced, algorithmically clustered and charted for instant insights and futher analysis.
  40. 40. Microsoft researchers are teaching AI to write stories about groups of photos https://ventu