804.424.1933 brad@bbbox.io

1 – Intro

I chose to use my existing business website blog functionality because A) I’ve already go this thing setup and I pay money for it, and B) who knows — maybe some of the thoughts I suss out for this Information Computing and the Future course can be refined into “thought leadership” I can use to promote Big Big Box.


2 – Questions & Source of Interest

I don’t have any initial questions. I’ll say that I’m excited to be taking this course and that I’ve been a “futurist” nerd for quite some time. In undergrad, my career plan was to become a neuroscientist, and this was just as the federal government was making a big to-do about investing in mapping the brain (Connectome Project), similar to the Human Genome Project. While going down that rabbit hole, I got into topics like the singularity, crowd-sourced problem solving via computers (like protein simulation by humans that out-performs supercomputers), AI/machine learning, and rethinking human interaction with technology (e.g., augmented and virtual reality, especially as Google Glass was being developed). Alas, I ended up doing Teach For America, got knocked off track, and I have been on a public service career path for the past decade. I’m earning a Master’s degree in information science because I’m hoping to apply data science knowledge and skills to make a bit of a career shift from communications and marketing for nonprofits to launch a career in marketing and advertising. Perhaps I can use these new skills to do some good along the way too….

I received the email flyer about this course, and it in a way re-kindled my love for futurism. As it’s not necessarily been an in-vogue topic of conversation within my professional and friend networks over the years, I’ve invested less time in learning and thinking about the future. However, I try to stay “in the know” about the latest tech trends by listening to podcasts and keeping an eye on various blogs and news articles.


3 – Michio Kaku’s 3 Predictions

On Michio Kaku’s site Big Think, the futurist shares “3 Mind-Blowing Predictions about the Future” (January 4, 2021).

I’ve followed Dr. Kaku over the past decade, and he’s always held my interest. I like his grounded claims, and he typically makes “predictions” by just expanding upon what’s already happening in current technology and science trends.


4 – Ninedi Okorafor Imagines a Globally Inclusive Future

Folks who’ve shaped the future have all too often either forgotten or marginalized people who’ve been othered. The Transcontinental Railroad was built by people of color who toiled and often died building the arteries for the United States’ growing economy, the avenues for capital that divided and even destroyed communities. As the modern American dream was shaped and born after WWII, people of color were banned through policies like “redlining.” Less destructive but equally telling, racial discrimination has been embedded in the development of “smart” technologies, like facial recognition. And a cursory glance at the portraits of futurists who captured public attention and imagination at the turn of the 20th Century will include older white men.

In her TED Talk “Sci-fi Stories that Imagine a Future for Africa,” author Nnedi Okorafor reminds of us of the historical inequities built into our global systems and how historically, futurists have not looked like her or her people. Her talk underscores the social and reputational capital required to shape the future, and Okorafor claims that power for herself, reminding us to ensure that as we create the future, we’re inclusive and open to ideas from all peoples.


5 – Philanthropy and Nonprofits Just Want 2020 to End

At the end of a normal year, like 2019, Trista Harris shares predictions for the public service sector. But with the pandemic and a global civil rights movement, Harris bucks tradition and instead issues a clear call to action. Philanthropy and nonprofits no longer have the luxury of ignoring the future. As she says, “2021 is the year for building your future thinking skills as your number one strategic priority. There is nothing more important than this now. If you don’t take future thinking seriously, your organization won’t exist in the near term future.”

After having met Harris a couple of times, I’ll say I have enormous respect for her. I especially appreciate her perspective because, while she acknowledges the role technology plays in shaping what’s to come, she emphasizes the organizational and social systems that are at play as well. 


6 – Proof that I’m a Good Grad Student, I Bought a Book

If you check out the rest of my company’s website, you’ll see that I do a lot of do-goodery work. This book stood out to me because it seems, more often than not, when we talk about the future and the role technology plays, everybody oos and ahs about the opportunity to increase efficiencies and achieve more as a species. This book points out, however, how the algorithms that increasingly make decisions for us can serve as an extension and fortefier of historic marginalization and systemic barriers to education, wealth, and exceptional quality of life. From the book’s website:

We live in the age of the algorithm. Increasingly, the decisions that affect our lives—where we go to school, whether we get a car loan, how much we pay for health insurance—are being made not by humans, but by mathematical models. In theory, this should lead to greater fairness: Everyone is judged according to the same rules, and bias is eliminated.

But as Cathy O’Neil reveals in this urgent and necessary book, the opposite is true. The models being used today are opaque, unregulated, and uncontestable, even when they’re wrong. Most troubling, they reinforce discrimination: If a poor student can’t get a loan because a lending model deems him too risky (by virtue of his zip code), he’s then cut off from the kind of education that could pull him out of poverty, and a vicious spiral ensues. Models are propping up the lucky and punishing the downtrodden, creating a “toxic cocktail for democracy.” Welcome to the dark side of Big Data.

As you can see, I paid money to Amazon and everything!