aditidevdasbhoir

[aditidevdasbhoir]

Dark Data

Dark Data: Why what you don’t know matter

It’s a generation of information technology where we search, transfer and share many information or we can say data daily related to several topics and “Dark Data” is itself a very unique name which was made me curious and pushed me to listen to a very interesting conversation on the book Dark Data: Why what you don’t know matters by Professor David Hand [1]. Data is always essential details of everyone. We don’t like to share our important details with others, especially personal data we always keep secret, but knowing unknowingly sometimes we share it. In a discussion professor defines dark data very pleasantly, data which we can’t see; but sometimes it takes us to very bad and dangerous disasters. He also gave some real-world examples which clear the meaning of this small but exclusive term “Dark Data”. Some persons or groups of people intentionally use data to fulfill their malicious purpose, for example bank fraud or financial fraud, which is very serious and extreme crime, where some organizations or you can say companies use data to attract customers to make money. Now-a-days due to social media and other media platforms are becoming platform and also become a medium which intentionally and non-intentionally provide us incorrect news which many times hide the actual fact. Dark data not only resulting to wrong output, but professor also explains how we can detect dark data and how we can deal with it, here; there is one point which I like the most is we actually can take advantage of dark data which provide us better results by analysing and understanding data. This discussion gave me a bit of in-depth knowledge and understanding of some actual backend process of data.

Conversation happened between the host Dr. Waseem Akhtar and the guest professor David Hand. Professor David Hand is Senior Research Investigator and Emeritus Professor of Mathematics at Imperial College, London. His focused research topics include multivariate statistics, classification methods, pattern recognition, computational statistics, and the foundations of statistics. He has published 300 scientific papers and 32 books. One of his book is Principles of data mining this book he wrote for general people to understand and guide for data mining [2], also there is his very nice paper on Statistical fraud detection: a review [3] and an article on Statistical challenges of administrative and transaction data in Journal of the Royal Statistical Society [4]. He is also awarded many awards like Medal of the Royal Statistical Society, George Box Medal, Research Medal of the International Federation of Classification Societies.

References:

 [1]https://www.bridgingthegaps.ie/2020/03/dark-data-why-what-you-dont-know-matters-with-professor-david-hand/

[2]https://dl.acm.org/doi/10.5555/2462612#:~:text=Principles%20of%20Data%20Mining%20aims,future%20technical%20advances%20in%20the

[3] https://projecteuclid.org/journals/statistical-science/volume-17/issue-3/Statistical-Fraud-Detection-A-Review/10.1214/ss/1042727940.full

[4]https://www.semanticscholar.org/paper/Statistical-challenges-of-administrative-and-data-Hand/2aa8348a499fc3d6adceb90ac54d6e13f4c757b6#paper-header

[aditidevdasbhoir]

Technology

To everyone, privacy is the most important aspect of their life. For me, also, privacy of my data while using technology is a must. Recently I listened to a discussion on Philosophy and Ethics of Technology on https://soundcloud.com/bridging-the-gaps/philosophy-of-technology-with-peter-paul-verbeek There are many points which I like a lot, discussion initialized with people's negative approach to technology. As a person, we have everything we can do by using all our organs and using our thinking and understanding abilities, but now technology exists. We do our work using technology. That’s why somewhere people think that technology questions human existence. In discussion they talk about the philosophy of technology understanding, evaluating, asking the right ethical questions related to technology in the philosophy of technology. He also mentioned that technology is a medium to connect the world, by giving a small example of the telephone where we are not interacting with the phone, it is just a mediator through we interact with another person. A very nice part of the discussion is discussion about Phenomenology and post-phenomenology, where he said phenomenology is an approach to understanding the relationship between humans and technology and post-phenomenology is does relation with world via technology. Ethics is important when developing any technology. While developing it, developers always think about a future impact on society, as in the world of Artificial intelligence and robotics, ethics related to this need to be evaluated because, at some time, the ethical impact on the future is beyond the fact we consider it while making it. The professor also talks about his work and reports on the ethics of robotics. He explains how technology is developed sensitively because it does not just evaluate the ethical impact of society but can evaluate the impact of society on technology. It is up to humans how much we have used technology ethically, as we can see sometimes using information and social media platforms how technology is used for bad purposes. In the end, Professor nicely explains the philosophy of technology involve many points what is technology mean, how technology is design, how will people think about technology. 

The gust in discussion is Professor Peter-Paul Verbeek. He is excellent Professor of Philosophy of Technology at the Department of Philosophy of the University of Twente and he is Rector Magnificus of the University of Amsterdam. He is also chairperson of the Philosophy of Human-Technology Relations research group and co-director of the Design Lab of the University of Twente. He is also honorary professor of Techno-Anthropology at Aalborg University, Denmark and is chairperson of the UNESCO World Commission on the Ethics of Science and Technology (COMEST). His research focuses on the analysis, evaluation and responsible design of the relations between humans and technologies. He is currently working on four research Theorizing Human-Technology Relations, Ethics and Politics of Human-Technology Relations, Technology and Scientific Practice, Philosophy of Design, Art, and Technology. His work has received several awards a VENI award, VIDI award , VICI Award, membership of The Young Academy , the Borghgraef Prize in Biomedical Ethics in Leuven University, and the World Technology Award in Ethics 2016 (World Technology Network).  I have also gone through his other projects which is below

[aditidevdasbhoir]

Artificial Intelligence

In today’s technology world as a Computing student, I am always a proactive person who like to learn about new things related to technology. A discussion going on in topic Artificial intelligence where discussion is about their pros and cons, development and especially artificial intelligence future gave me bunch of knowledge. The discussion is on given https://www.bridgingthegaps.ie/tag/artificial-intelligence/  In a discussion I get to know about many things, initially I catch up with one point that do system understand? As we human we understand, and we can predict certain things in many situations, but machine not, even a machine not understand what they are doing, all the things are programmed, and they are acting as per their programming commands. Also, discussion come up with one more point that there is a lack of generalization in artificial intelligence as they can act wrongly if we made any changes or their atmosphere change in such circumstances generalization is important. Normally, we define Artificial Intelligence as a machine who act like human being. Now many Artificial Intelligence specialists are now trying to implement understanding in artificial intelligence to make machine really act like human as I said above, a machine many acts differently if we made changes in it but implementing understanding in machine can make them reliable and trustworthy. Yes, it is hard for developers to implement Artificial Intelligence system with this as there are very common things we think as human, but it is challenging to implementation in machine. There are some researches mentioned during discussion, Artificial Intelligence researchers collaborating with other field researchers to research deeply in it. In a discussion a very thinkable question rise in a context of future of Artificial Intelligence is machines become self-aware one day? Daily artificial intelligence come up with lots of new innovation and researches which make us think about this question. Yes, right now only we can just predict but cannot give surety about it. There are many of this Artificial Intelligence discovering and developing in a small as well as in a large platform. 

A great discussion I have heard ever which is by the guest professor Melanie Mitchell. She is professor of complexity at the Santa Fe Institute in New Mexico. Currently, she researches on genetic algorithms, Conceptual abstraction, analogy making and visual recognition in Artificial Intelligence system. She also an author of many books, one of her book is Artificial Intelligence: A Guide for Thinking Human, and also she wrote many papers related to artificial intelligence field. Also, her one book got awarded name Complexity: a Guided tour. I also read her some paper and research, which is very nice.