Author: ezucca

Eugenio Zuccarelli’s Data Log – 24th Feb 2020

Chatting with People

As usual, I used emails and Slack a lot throughout the day, mostly to schedule meetings and coordinate work, but also to just get in touch with friends. I texted friends with WhatsApp and, despite it claims end-to-end encryption, I also use Signal since it should be a more secure and privacy-focused app. Even if the content of the messages was not collected as plain text, it is most likely that encrypted information was still collected and logged, as well as my GPS position and time of the day. 

Moving Around Town

I walked from my dorm to the main campus, but my location has most likely been captured by apps running the background anyway. Later in the day, I took the T to Harvard and my travel got logged when swiping my T pass, while my face got caught from security cameras throughout the station. Throughout the day I also swiped my MIT ID Card to pay for food and access buildings, leaving traces around campus about my location and purchases.

Getting Online

I stayed online for most of the day with my Google account logged in, using a multitude of applications which must have been captured by Google. I also logged into specific websites that require registration such as news sites like The New York Times, Bloomberg but also my MIT and Harvard accounts. Throughout the day I checked social media, scrolling through my feed. This allowed these websites to track a wide range of information, from my position to the links I clicked, posts I liked and videos I watched, adding up to the user profile they already have on me.

Other Things

I am pretty sure there is a whole range of apps and systems collecting my information with me not even realizing it. For instance, I might have granted too many permissions to a few apps, which are collecting a wide range of data even in the background.

Navigating Buzzwords

Data presentation blog post by Eugenio Zuccarelli

Source: Gartner

In a world filled with buzzwords ranging from Internet of Things to AI and Edge Computing, navigating the innovation space can be quite tricky.

One aspect shared by mostly all the innovative technologies though, is the general trend they follow, starting from low key discoveries, until reaching maturity and widespread use.

Gartner, a global research and advisory firm, developed a general framework that captures all innovative technologies and maps them into a specific framework.

This framework, called Hype Cycle for Emerging Technologies, shows the general trend followed by technologies over time, mapping society’s expectations towards each innovation.

In particular, the chart lists all current technologies on x-y axes, where the position determines the general expectation over time. The innovations start from an “Innovation Trigger”, propelling them to peak hype, then to a minimum point for then coming back again at a more moderate pace, reaching stable progress.

By showing such information in a conceptual form, rather than being data-heavy, the Hype Cycle can be used to reach any audience. Indeed, the simple and relatable concepts expressed by the chart can be understood by any person with knowledge of the “common buzzwords”.

However, the chart can be even more useful for technical people, with a strong understanding of the technology environment that can benefit from using or investing in the technology.

Overall, the Hype Cycle aims at giving context to emotionally-inflated concepts such as AI, IoT and Cloud Computing. These concepts are usually able to capture the interest of the masses, but then showing similar patterns of disillusionment. Here, Gartner’s cycle successfully clarifies that some technologies are still in the early stages and overinflated, while other technologies have almost reached maturity, and are ready to become part of our daily lives.