In conversation with: Jennifer Zhu Scott

In conversation this time is well-known finance and digital economy expert, Jennifer Zhu Scott. Jen recently joined the WST Board of Trustees and we are delighted to welcome her. Ian Brown sat down to find out a little more about Jennifer’s (Jen’s) path to Web Science and why she thinks we’ve invented a whole new kind of poverty and what we should be doing about it.

Ian: Hi Jen, welcome to the Trust and thanks for joining us today to give the WST members and supporters an idea of who you are and where your interests lie.

Jen: No problem – I’m really pleased to be joining the board at a time when there is so much important work to do.

Ian: Like many of us you didn’t start out as a Web Scientist but reading your Bio you have studied very widely across different disciplines in Sichuan, Manchester and many top institutions – that’s quite a journey – can you tell us a little about it?

Jen: I was brought up in an environment where my father was always tinkering, disassembling and reassembling radios, fixing lights and telephones. I was very comfortable with technology. When I was in university, I bought the parts and built my own PC. Technology and science is my native language. I remember being fascinated by what technology could do. Today, as a professional, it is evident that technology has transformed every aspect of our life. Whilst our understanding of technology leaped ahead at a breakneck pace, our understanding of the social impacts of technology (the socio-technological aspect)  has been moving much, MUCH slower. I knew there must be trade-offs between what technology could do and what it should do but there didn’t seem to be any good models or guidelines for that. Arguably there still aren’t.  

My studies started with Applied Maths & Computer Science and when I left China I came to the UK to work and later on studied Finance in my master’s degree. Data is the essence of every discipline I’ve studied. I moved into industry working for some big FinTech data companies looking at how advanced technologies could be applied to businesses individually and what the key trends would be in (digital) value.  However, I was still interested in how all these benefits could be distributed across society more broadly and continued my studies branching into public policy – trying to understand how policy is formed and how change is driven on a larger scale.

 

 

Ian: You mentioned the importance of data and you gave a TED talk in 2019 about data and why we should be being getting paid for it

Jen: Absolutely. We are supposed to work towards a more inclusive and equitable economy, but in terms of data ownership, most of us are just equally poor. Most people haven’t understood the concept or implications of data poverty. The thing I learned in China as a child is that ownership, personal ownership, brings a form of liberty and the opportunity for improvement. At a time when seven of the top 10 companies on the planet derive their wealth from data about us, the conclusion is that data is immensely valuable – but the power struggle for the ownership and control of the data has only been between corporates and governments, and individuals have no seat at the table, yet the vast majority of data is generated by individuals.  My proposal of establishing the economic value of individuals’ data with a degree of pricing power is a way to grant the individuals’ rights in a digital economy and reflect each individual’s nuanced need for privacy.

Ian: I think it’s widely accepted that when a product is offered for free it is generally the users who are actually the product. I like to think of it as receiving “free shovels” that we use to dig up all the vegetables in our garden and give away to the supermarket where we can go to buy them back! 

Jen: I would argue that in the case of the current economy, we are not even a product. Shoshana Zuboff writes in her book “The Age of Surveillance Capitalism” that we are only raw materials in the current digital economy. I tend to agree with her. We also give away our time, privacy, and mental wellbeing to constantly produce data for big tech.  I argue that in many ways our ‘free will’ is an illusion – a result of algorithms to manipulate more attention and more ad clicks. Therefore, a nuanced reflection of our privacy, health and individual priorities in our digital life is an important pillar of a fair and inclusive digital economy.

Ian: That is a constant problem on the Web – finding models that fit everyone globally.

Jen: In Europe, California, and increasingly China, the regulators approach this problem with more and more limitations and regulations. In China, to respond to centralized sensitive data collection and control, the regulators are introducing data localization rules to protect national security. There are more than 60 regulators around the world that are working on more than 150 various data localization rules. But the web is supposed to transcend borders and jurisdictions. Instead of forcing a balkanization of the World Wide Web, we should enable and empower decentralized data control and ownership that puts the individual at the center. With a decentralised model, it would be harder for one corporate to put national security at risk. 

Ian: We are seeing a lot of debate about Elon Musk’s proposal to change policy at Twitter if/when he buys it. In simplistic terms are we trading free speech against hate speech?

Jen: Twitter has become a tremendously powerful platform with its algorithm driving political and social discussions around the world and whether or not Elon believes he is championing free speech for all the right reasons we have to question whether one person should be making decisions with such a huge potential impact for hundreds of millions of people around the world. Elon is using his position to improve things as he sees them, but ultimately even a “better Emperor” is still an Emperor.

Ian: So you are suggesting more regulation of these types of technologies?

Jen: As we discussed, global regulation may not always be appropriate at the local level – this is where public policy comes in. There is an important difference between asking HOW something is done and if something SHOULD be done. Technology is a bit like medicine – we should be exploring, developing, and investigating what is possible without necessarily automatically licensing/approving every discovery, everywhere before understanding the costs, trade-offs, and local impacts.  This is about value-driven leadership  – moving beyond profits towards benefits and improvements for society as a whole.

Ian: But would you support the large-scale use of personal data in some cases? Some people argue that small amounts of data “don’t count” ..

Jen: Arguing that individual data doesn’t count is like arguing that one vote doesn’t count – it’s the principle that counts and it certainly matters to the individual. Data at scale is valuable of course – the question is who has the control. I chair The Commons Project, a tech non-profit that’s working towards interoperability and global health data standards that will allow us to respond to national and international events like pandemics by quickly sharing data between different countries and labs globally so the borders won’t need to shut down for so long. Covid has shown us the need to be able to react quickly and globally. At The Commons Project, we do not monetize individuals’ data. While there is a large amount of data in the mix, we minimize the data collection and maximize privacy protection. With the right governance model, you can build tech that puts the people at the center.

Ian: So with use cases like this that employ global technical standards for health data where is the place for Web Science?

Jen: Web Science brings together a host of interdisciplinary approaches from technology, law, philosophy, medicine, government (and many more) to examine the issues and decide the most important questions; even if we can do something, when/where is it appropriate to do so? How can we do it so there is clear accountability to the people and society? 

Historical medical data about a terminated pregnancy might inform health policy generally and future medical treatment for that one patient specifically but it might also get that patient prosecuted, imprisoned (or worse) in certain legal jurisdictions, or where policy/public opinion may change over time. We need to think beyond the narrow impact (or profit) in the present and consider the longer-term, wider strategic impact of these decisions.  

Ultimately the question is much more nuanced than “how can we capture/store the data?”.

In China, the ride service DIDI collected detailed journey/location information on over 550 million passengers and 10’s of millions of drivers. DIDIs aggregated data on billions of journeys offered detailed maps/models of locations that were not even on official maps and that showed who had been where and when. When attempting a foreign (US) listing in 2021 the Chinese government became uncomfortable about the international security and privacy implications of the data and has moved to restrict DIDI’s operations through the removal of the associated apps from mobile platforms as well as an investigation of the company’s potential abuses of personal data.

It goes to show that data and networks of data “at scale” have very different social implications to smaller private data stores – Web Science focuses on these types of networks at global scale.

Ian: What do you see as the role of Web Science going forward? What would you like to see happen?

Jen: We should be looking to educate users about how their data is used, how valuable it is, and why they should be managing it better. In Web2, companies like Facebook have data monetization baked into their business model. Their algorithm is designed to hook users to spend more time on their site because ‘time on site’ is an important determinant of advertising pricing. What the algorithm discovered is that when people are angry they tend to stay engaged for the longest time. This is why platforms like Facebook are full of divisive, provocative content that’s designed to trade your rage for advertising dollars. We live in a more and more polarised and divided world so Mark Zuckerberg can become a multibillionaire. Web Science Trust should gather the brightest minds in the world in our field to actively educate, debate, participate and build a healthier digital world.  There are so many more issues to address – how AI interacts with our data, the responsibility for the algorithms, the crypto-asset bubble, the lack of security and value model for NFT and the list goes on. It all centers around data: the use of data. the value of data, the ethics of data, and the ownership of data.

If our view of the world on the Web (what we see and what we are served up via search and social media) remains so strongly controlled by a combination of a data-centric 360-degree profile of our activities and profit-centered algorithms then I would argue that it’s not only a huge privacy issue, as people have argued – our freedom of information, our freedom to choose and, with it, our free-will are severely impacted. Does free will actually become an illusion?   

We need an impactful, multi-disciplinary conversation about data: its value, its uses, its ownership, and its potential benefits for society – that is where Web Science can and must make an impact.

Ian: Jen – thanks for joining us and once again welcome to the Web Science Trust!

In Conversation with: Bill Thompson

What do you get when you mix Philosophy, Applied Psychology, AI, Political activism and Unix programming with the Web?

In conversation this time is well-known BBC journalist, author and technology pundit Bill Thompson, who is surely an obvious candidate for the titles of both renaissance man and Web Scientist – he recently joined the board of Trustees at WST and we are delighted to welcome him. Ian Brown sat down to find out a little more about Bill’s road from Philosophy to Web Science and why he has been “thinking about the way the network is changing the world”.

Ian: Bill, you left Cambridge with a degree in Philosophy (with a side interest in Experimental Psychology) and decided to stay in Cambridge (post grad) to take a Diploma in Computer Science – how did that mix of disciplines shape your thinking?

Bill: I had initially been interested in the philosophy of mind and, from there, to how minds work (psychologically) and then whether it might be possible to build minds (machines that sense and think) using neural networks and artificial vision. From there I became interested in human-computer interaction and started to think more about how to build machines that might amplify our own minds.

Ian: What was the state of the tools available at that time to tackle those goals?

Bill: Well the technologies were starting to emerge – I joined Acorn just as someone was saying “what if we did something different and created a RISC processor..?” which was pretty interesting. As I moved through roles at Pipex and The Instruction Set I learnt more about programming, databases and networking and I attended the very first WWW Conference meeting Tim Berners-Lee (one of WST’s founders) in the process. Looking back I was on the periphery of some very interesting projects and impressive characters in AI and the Web throughout much of my education and early career.

Ian: Did you have a sense back then of how important these technologies were going to be and did you have a feeling whether the people were driving the technology or vice versa?

Bill: I think my views came together slowly over a decade between ‘84-‘94 culminating in helping to run a national body called the Community Computing Network through a growing sense of what computers could do for society and the social and political impact of technology. We wanted to help people see computing for what it could do socially as well as technically.

I think there was a sense of anticipation that technology could level the playing field between big businesses (or even oppressive states) and the rest of us – we were telling charities to embrace the same computing technologies as the big players with our slogan “If it can do it for them – it can do it for you! “. We realised we had to consider how technology is applied and not only the tools themselves. We wanted people to get engaged in owning/shaping their technologies for better social outcomes.

Whilst I had initially developed my thinking in the HCI world, I started to run into people (including Nigel Shadbolt – a fellow WST trustee) talking about Web Science – an approach that seemed to crystallise many of the things I had been thinking about in terms of interdisciplinary boundaries and adaptive models to describe fluid conditions and new technologies – in effect “thinking about the way the network is changing the world”.

Ian: I typically ask my “In conversation” guests which part(s) of Web Science particularly interest and attract them but I understand you’ve come up with a different definition of Web Science which addresses the moving target issue in Web Science.

Bill: I’ve really side-stepped the difficulties in defining what an ever-changing Web Science is by taking a cue from pragmatic Philosophy and focussing instead on what Web Science does* and, more importantly asking, “What do we need from Web Science?”. Web Science can usefully be defined by what we need it to do at any given point.

Ian: So let me ask you instead what do we need from Web Science now and is it the same as we needed when Web Science was founded over a decade ago?

Bill: Whilst its difficult to point to specific examples I think we need to understand (in a changing environment) where we can have most leverage to deliver the outcomes we think are most desirable for society as a whole. With 3 billion extra people coming online soon and technologies becoming more pervasive every year I think we are going to see a number of “step changes” in the Web we know today and a need to determine which aspects of this vast and growing system of interacting technologies that will need to be regulated. We can’t expect to build technologies with global reach and so many effects, both positive (e.g. economic) and negative (e.g. social/climate) effects and simply leave the world to cope. Web Science needs to research, reflect and advise on the impacts and (dis)benefits of these approaches, bringing a strong evidence-based historic viewpoint which will allow us to effectively learn from the past as we plan for the future – something which seems sadly lacking from the approach of some modern tech companies.

Web Science can help us to see that technology can be grounded in humanity and human processes in a rigorous and useful way. We can help people that aren’t really “noticing” these invisible/pervasive technologies by making clear to them that whilst society is indeed moulding the Web, the Web is also moulding society at the same time. I’ve been saying for the last 20 years that we need to stop thinking of “the Web” and “Cyberspace” as distinct places – they are simply new ways of expressing society and humanity with everything ultimately grounded in the real world with real-world costs and consequences.

There are many new freedoms (both positive and negative) that become possible on the Web. We need a level of rigour to balance those personal freedoms against the social responsibilities that maintain the Web as a viable and positive experience. Perhaps we need to be the “anti-poets” in this venture.

Ian: Bill, thanks for joining me in conversation – we look forward to another session soon.

Bill Thompson is an English technology writer, best known for his weekly column in the Technology section of BBC News Online and his appearances on Digital Planet, a radio show on the BBC World Service. 

He is a Trustee of the Web Science Trust (WST), an Honorary Senior Visiting Fellow at City University London’s Journalism Department, He is chair of the Centre for Doctoral Training advisory board, a member of the main advisory board of the Web Science Institute at the University of Southampton and writes for BBC Webwise.

Posting: Rutgers

Tenure-Track/Tenured Faculty Position in Data Science and Organizations/Organizing

 The Department of Communication at Rutgers University’s School of Communication and Information seeks a full-time faculty member (likely assistant or associate level) in the area of Data Science with an emphasis on Organizations and/or Organizing. The appointment will begin Fall 2022.

 We seek a social scientist studying organizations and organizing who incorporates data science methods into their research. The ideal candidate will conduct theory-driven, empirical, communication-centered research that examines dynamic processes of organizing. We are looking for innovative and engaged communication scholars whose research foci recognize emerging issues, including but not limited to:

  • Organizations, work, and equity
  • The science of work groups and teams
  • Artificial intelligence and the future of work
  • Media and technology
  • Organizations and technology
  • Globalization and civil society
  • Organizing and collective action
  • Organizational networks

The ideal candidate will have expertise in core methods related to data science including, but not limited to, any of the following:

  • Machine learning
  • Natural language processing
  • Network science

Our faculty employs a wide range of empirical approaches in their research. We encourage candidates whose scholarship intersects with, and extends, one or more of the department’s research foci (organizational communication, health communication, communication and technology, interpersonal communication, and language and social interaction) and/or other areas within the school such as media studies and information science. For more about the Department of Communication and the School of Communication and Information (SC&I), see http://comminfo.rutgers.edu 

 We look forward to welcoming a new colleague who will contribute to our thriving undergraduate and master’s level programs and our highly-regarded interdisciplinary school-wide Ph.D. program.

 

MINIMUM EDUCATION AND EXPERIENCE

 A Ph.D. or equivalent doctoral degree in a relevant field is expected as of June 2022 for a September start date.

 Applicants should have a demonstrated record or strong likelihood of top-tier peer-reviewed publication and evidence of or preparation for effective teaching. Applicants at the rank of Associate Professor should provide evidence of leadership in research, instruction, and service; a record of external funding is a plus. Responsibilities of tenure-track and tenured faculty members include undergraduate and graduate teaching assignments, an active program of research in the candidate’s area of scholarly expertise, and service contributions in accordance with the university policy for tenure‐track and tenured appointments.

 

OVERVIEW OF THE SCHOOL

Rutgers, The State University of New Jersey, is a leading national research university and the state of New Jersey’s preeminent, comprehensive public institution of higher education. Established in 1766, the university is the eighth oldest higher education institution in the United States. More than 70,000 students and 23,400 faculty and staff learn, work, and serve the public at Rutgers locations across New Jersey and around the world. An equal opportunity and affirmative action employer, Rutgers is committed to building a diverse community and encourages women, minorities, veterans, and individuals with disabilities to apply. We are currently in an exciting period of transformation and growth as we form a hub for data science across departments at Rutgers University.

 

The School of Communication and Information (SC&I) is a dynamic center of learning at the heart of the Rutgers-New Brunswick campus. Founded in 1982, SC&I research and teaching is delivered by three academic departments: Communication, Journalism and Media Studies, and Library and Information Science. Through five undergraduate majors and minors, three masters degrees, and an interdisciplinary Ph.D. program, the school teaches over 10,000 students each year, of whom 2,500 are its own undergraduate, masters, and doctoral students. Geographically adjacent and closely connected to the world’s largest media and information hubs and supported by Rutgers’ vibrant scholarly community, SC&I embraces the university goals of promoting diversity throughout our networks and programs, and is committed to social engagement. For more about the school see: http://comminfo.rutgers.edu 

 Inquiries can be made to the search committee chair: Professor Matthew Weber (matthew.weber@rutgers.edu), Department of Communication, Rutgers University, 4 Huntington St., New Brunswick, NJ.

 Rutgers University is an AA/EEO employer – M/F/Veteran/Disability. 

For additional information please see our Non-Discrimination Statement.

TO APPLY

Review of applications will begin on September 27, 2021, and will continue until the position is filled. Candidates are required to submit a letter of application, CV, two sample publications and the names of 3 references. All applications must be submitted through the online job posting at https://jobs.rutgers.edu/postings/135500 

Guide to [US] Colleges & Careers for Women in STEM

There’s no denying the importance of those working in STEM (Science, Technology, Engineering and Math) occupations. In fact, it’s nearly impossible to imagine what our world would look like without the advances that have been made in these fields. They’ve brought us vaccines that have cured diseases, deepened our understanding of the universe and given us tools that make us more connected than ever before.

Job growth in STEM fields continues to outpace that of all other occupations, too. According to the U.S. Bureau of Labor Statistics, jobs in these industries are projected to grow by nearly 9% between 2018 and 2028, compared to an even 5% for all non-STEM occupations.

Unfortunately, due to gender biases, fewer role models and male-dominated industries, women have been historically underrepresented in STEM. Despite common sense and plenty of research showing no cognitive difference between men and women, the myth that women aren’t as good at math has broken the confidence of many young girls. It doesn’t take long, either – by 3rd grade, that misconception is already creating a gap and by college, it’s a chasm – women represent only 21% of engineering majors and just 19% of computer and information science majors.

Overcoming this gap is critical. Not only will it help open more opportunities for women currently in the field, but it will also create more role models, help shatter stereotypes and introduce new talent and fresh perspectives to these fields.

PLEASE NOTE study.com is a commercial site and the listed schools which accompany this article are

(1) limited to the US and

(2) include sponsored/paid listings.

Read the full article on study.com here