Information Asymmetry and Costly Signaling: What Bitcoins Can Teach

There is a dramatic, rapidly growing, information asymmetry among political agencies, advertisers, web based companies and individual users. While this asymmetry appears to make the situation “unfair” only to a subset of individuals, in reality, it also introduces undesirable global effects which can include, for example: (i) it can be inefficient, (ii) it can lead to deceptive practice and (iii) it can challenge the inherent altruistic norms. The rise in information collection about users, the wholesale aggregation of this information, and the widespread application of machine learning has exacerbated the information asymmetry. When a user does not know much about a website's utility function, he or she can be even more likely to be on the losing side of the transaction. The solution of migrating to another planet/country, not using the web, being anonymous, using HTTPS, and the use of encrypted information, can just provide temporary relief by addressing only minor annoyances. We will describe a possible fix using costly signaling in a way similar to what Bitcoins use.

https://www.google.com/patents/US20170011330

Professor Bud Mishra is a professor of computer science and mathematics at NYU's Courant Institute of Mathematical Sciences, professor of engineering at NYU’s Tandon School of engineering, professor of human genetics at Mt. Sinai School of Medicine, visiting scholar at Cold Spring Harbor Laboratory and a professor of cell biology at NYU School of Medicine. He founded the NYU/Courant Bioinformatics Group, a multi-disciplinary group working on research at the interface of computer science, applied mathematics, biology, biomedicine and bio/nano-technologies. He has industrial experience in Computer and Data Science (aiNexusLab, ATTAP, behold.ai <http://behold.ai>, brainiad, Genesis Media, Pypestream, and Tartan Laboratories), Finance (Instadat, Pattern Recognition Fund and Tudor Investment), Robotics and Bio- and Nanotechnologies (Abraxis, Bioarrays, InSilico, MRTech, OpGen and Seqster). He is the author of a textbook on algorithmic algebra and more than two hundred archived publications. He has advised and mentored more than 35 graduate students and post-docs in the areas of computer science, robotics and control engineering, applied mathematics, finance, biology and medicine. He holds 21 issued and 23 pending patents in areas ranging over robotics, model checking, intrusion detection, cyber security, emergency response, disaster management, data analysis, biotechnology, nanotechnology, genome mapping and sequencing, mutation calling, cancer biology, fintech, adtech, internet architecture and linguistics. His pioneering work includes: first application of model checking to hardware verification; first robotics technologies for grasping, reactive grippers and work holding; first single molecule genotype/haplotype mapping technology (Optical Mapping); first analysis of copy number variants with a segmentation algorithm, first whole-genome haplotype assembly technology (SUTTA), first clinical-genomic variant/base calling technology (TotalRecaller), and current work in progress continuing in the areas of liquid biopsies (with Jee, Nudler et al.), cancer data (with Antoniotti, Bannon, Cantor, Grossman, Korsunsky, Rabadan, Ramazzotti, Zhavoronkov et al.), cyber security (with Casey, Morales, Novak et al.), cryptography (with Gvili, Janwa, Kahrobaei et al.), linguistics (with Chakraborty, Rinberg, Tamaskar, Young et al.) financial engineering (with Deboneuill, Subramaniam, et al.)  and internet of the future (with Rudolph, Savas, Weill et al.). Prof. Mishra has a degree in Science from Utkal University, in Electronics and Communication Engineering from IIT, Kharagpur, and MS and PhD degrees in Computer Science from Carnegie-Mellon University. He is a fellow of IEEE, ACM and AAAS, a Distinguished Alumnus of IIT-Kgp, and a NYSTAR Distinguished Professor.