This news has been a few months in the making, but with the final preparations underway, I feel like it’s time to announce it! In a few weeks, I will be launching my podcast series – Stories from Space – with the Intersection Of Technology, Cybersecurity, And Society Podcast (ITSP), a highly-respected channel that hosts multiple shows. Each of these is dedicated to exploring the past, the present, and the future of humanity’s relationship with technology and the profound effects it can have on our society.Continue reading “Good News! Stories from Space Picked up by ITSP Magazine!”
The good people over at Envisioning Technology – the independent research organization based on Brazil – have produced yet another intriguing infographic. As some of you may recall, whenever ET has released a new inforgraphic, I’ve been right there to post about it. So far, they have produced graphics addressing the future of Technology, Education, Health, and Finance.
There latest graphic is similarly significant and addresses the future of something that concerns and effects us all: money. Entitled “The Past, Present and Future of Money”, this graph looks at the trends affecting the buying, selling and investment patterns of people over time, contrasting three trends that are interwoven and have moved between centralized, decentralized, and distributed monetary systems.
In this scenario, centralized tendencies refer to networks where the nodes are connected through dense centers (aka. urban environments), which rely on hierarchically structures institutions (i.e. banks) and require legal tender (physical money). This sort of system relies on an ordered distribution of power, one that generally favor the connected few, and which emerged with the advent of modern industrial civilization.
Decentralized tendencies are those which are based on networks where nodes connect in clusters, that have irregular distributions of power, and favor the selected individual. As the graph shows, these types of networks predate centralized networks, taking the form of bartering and commodities in earliest times, but which have emerged yet again in the modern era and are predicted to continue to grow.
Examples of current and future trends here include crowdsourcing, crowdfunding, banking APIs (Application Programming Interfaces), microfinance, and collaborative consumptions – where access is developed so that consumers can lend, swap, barter, share, and gift products. Whereas this model predates centralized tendencies, it is once again emerging with decentralizing potential of digital technology and open-source databases.
In the third and final method, one which is emerging, is the distributed network of money. These are networks where nodes connect independently, where power is distributed horizontally, and which favor the entire network. This trend began as a result of global real-time communications (i.e. the internet, satellite communications, etc.), and which are expected to expand.
Combining the concepts of attention economies, digital currencies, peer-to-peer communications, and digital wallets, the essence of this final stage is a network economy that is controlled by individuals, not financial institutions or corporations. In addition, currencies are based shared belief in their value, transactions occur between individuals, and physical currencies are replaced by digital ones.
Other trends that are incorporated and cross-referenced into this infographic include global population versus the number of people per capita who have online access. As it stands, less than half the world’s 7 billion people currently have access to the internet, and are hence able to take part in the decentralizing and distributed trends affecting money. However, the infographic predicts that by 2063, nearly 90% of the world’s 10 billion people will be online.
Like many predictions that I’ve come to know and respect, this latest infographic from ET gives us a glimpse of a future where a Distributed model of politics, economics and technological development – otherwise known as Democratic Anarchy – will be the norm. It’s an exciting possibility, and places history in a new and interesting light. In short, it makes one reconsider the possibility that true socialism might exist.
While this was crudely predicted by Karl Marx, the basic concept is quite intriguing when considered in the context of current trends. What’s more, subsequent thinkers – Max Weber, Proudhon, Gramsci and George Orwell – refined and expressed the principle more eloquently. Nowhere was this more apparent than in the Goldstein Manifesto in 1984, where Orwell addressed how the process of industrial civilization was making class distinction virtually unnecessary.
For some time now, classroom cameras have been used to see what teachers do in the course of their lessons, and evaluate their overall effectiveness as educators. But thanks to a recent advances in facial recognition software, a system has been devised that will assess teacher effectiveness by turning the cameras around and aiming at them at the class.
It’s what’s known as EngageSense, and was developed by SensorStar Labs in Queens, New York. It begins by filming student’s faces, then applying an algorithm to assess their level of interest. And while it might sound a bit Big Brother-y, the goal is actually quite progressive. Traditional logic has it that by filming the teacher, you will know what they are doing right and wrong.
This system reverses that thinking, measuring reactions to see how the students feel and react, measuring their level of interest over time to see what works for them and what doesn’t. As SensorStar Labs co-founder Sean Montgomery put it:
This idea of adding the cameras and being able to use that information to assist teachers to improve their lessons is already underway. Where this is trying to add a little value on top of that is to make it less work for the teachers.
Montgomery also emphasized that the technology is in the research and development research and development phase. In its current form, it uses webcams to shoot students’ faces and computer vision algorithms to analyze their gaze – measuring eye movement, the direction they are facing, and facial expressions. That, coupled with audio, can be transformed into a rough, automated metric of student engagement throughout the day.
After a lesson, a teacher could boot up EngageSense and see, with a glance at the dashboard, when students were paying rapt attention, and at what points they became confused or distracted. Beyond that, the concept is still being refined as SensorStar Labs looks both for funding and for schools to give EngageSense a real-world trial.
The ultimate goal here is to tailor lessons so that the learning styles of all students can be addressed. And given the importance of classroom accommodation and the amount of time dedicated to ensuring individual student success, a tool like this may prove very useful. Rather than relying on logs and spreadsheets, the EngageSense employs standard computer hardware that simplifies the evaluation process over the course of days, weeks, months, and even years.
At the present time, the biggest obstacle would definitely be privacy concerns. While the software is designed for engaging student interest right now, it would not be difficult at all to imagine the same technology applied to police interrogations, security footage, or public surveillance.
One way to assuage these concerns in the classroomstudents, according to Montgomery, is to make the entire process voluntary. Much in the same way that smartphone apps ask permission to access your GPS or other personal data, parental consent would be needed before a child could be recorded or their data accessed and analyzed.