Turn Back Time With These 5 new Technologies

While the world is steadily moving toward a future with AI, autonomous cars, and potentially Skynet, some allege that the future might better resemble the past than anything new.

Fintechpreneurs like Elon Musk and companies like Google lead the world in innovative ideas and innovative technology. We are close to using serviceable exoskeletons as prosthetics and beneficial augmentations. Vertical farming efficacy is debated yet still a novel idea and application of modern agricultural and structural advancements.

Even lab-grown food is gaining traction.

So why are some innovators “turning back the clock” with outdated approaches and why does that matter?

5 Ways Tech is Working Backwards (for Better or for Worse)

1. Future Planning: Cities Not Dominated by Cars

City planning is a constantly moving target varying with population, topography, and other factors constantly evolving as our society advances. Yet, while some are imagining futuristic cities, other innovators are channeling their medieval ancestors.

In the very-ideal-future world (think post-scarcity), cities may have no need for cars.

We may even have teleportation (a girl can wish, right?).

David Galbraith, former architect and protege to the mind behind Apple’s “Space HQ”, claims that the “spatial rigidity” of today’s cities won’t have a place in the future.

“We think of self-driving cars as being a disruption of the way cars work, but they’re probably going to disrupt public transit just as much, because you’re going to be able to hail your own train car,” says Galbraith

The future necessitates a new approach to city planning. Due to his ability to always be ahead of the curve, Elon Musk is also developing solutions for this.

2. Antibiotic Innovation & Research

Research into antibacterial peptides and CRISPR technology may be integral in the creation of antibiotics for future diseases and infections. This means we need to protect the bees.

A compound with antimicrobial properties known as AP137 is the subject of a recent study from UIC researchers and co-investigators Nora Vázquez-Laslop and Alexander Mankin of the College of Pharmacy’s Center for Biomolecular Sciences.

Found predominantly in bees, wasps, and hornets, studying the way this peptide attacks proteins could yield useful, new antibiotics.

Since virtually no new antibiotics have been created in 30 years, the search for different ways to combat superbugs is an important one. But targeting specific strands of DNA or compounds might not be the only route to innovation.

Not So Mad Science

Kevin M. Folta, a professor at the University of Florida, had an epiphany whilst trimming his yard.

“…instead of inserting DNA information we understand, what if we introduced a scrambled mess of random DNA code into a plant or bacterium? Could we identify random bits of genetic information that could give rise to small proteins (called peptides) that change an organism’s physiology or development?”

Folta’s logic is that the “scrambled mess of random DNA” would force the organism to create an entirely new strand of DNA in response. He elaborates saying that most of the time, it would be “cellular rubbish”, but there might that one-in-a-million strand that’s world-changing. As a result of testing this hypothesis, intriguing yields raised further questions.

Why did some plants flourish, growing longer leaves or showing more intense pigments while others grew stunted? Why did others grow to a certain point and then suddenly die? While the cause is yet unknown, Folta says that we are on the brink of discovery and we can’t stop with plants.

“Some of these peptides must interfere with an important biological process because they kill the plant.”

In a move away from targeted research, randomized tests will potentially yield more robust antibiotics in the future–and just a little mad science.

Speaking of Tolerances and Resistances:

3. Pesticides

While the jury is quite out when it comes to the long-term effects of pesticide use in humans, the effects are much more evident in our amphibians cohabitors.

Amphibians–as in frogs. Though far removed from human anatomy, leveraging both flora and fauna in the search for improved pesticides is the future. Blanketing a field in chemicals doesn’t fly anymore and, like antibacterial soap that kills 99% of bacteria, it could potentially kill the good stuff, too.

What Effects on Frogs Mean for the Future of Disease

As a result of prolonged exposure to pesticides, amphibians develop increased vulnerabilities to parasites. This has to do with the combination of variables and not just the pesticides cites Jessica Hua, Assistant Professor of Biological Sciences at Binghamton University.

“Not only do different stressors interact in ways that can be difficult to predict but evolutionary responses to one stressor can shape amphibian responses to other stressors. This work highlights the importance of considering ecological and evolutionary processes when evaluating the effects of contaminants.”

Hua and her team continue research thanks to a grant from the National Science Foundation.

Their focus is using an interdisciplinary approach to investigate how evolved pesticide tolerance and use of land affect disease outcome. This research also reinforces an old lesson: life evolves, but at a cost.

4. From Gaydar to Sexism: Antiquated Stereotypes in AI

Machine learning and deep learning are tools for the future of artificial intelligence. But, they fall victim to classic human biases. As a result of this susceptibility, algorithms or AIs utilizing machine learning develop these biases and showcase them quite fabulously.

Some people often claim they have insanely accurate “gaydar”–the ability to determine whether or not someone is gay. Naturally, someone is developing tech to detect a person’s sexual orientation by their face. Much like the predictive algorithm from the University of Washington which we covered recently, this algorithm shows bias.

Despite staggering results (81% accuracy for men and 74% for women), the neural network utilized facial structure in order to determine sexual orientation. It claimed that gay men and women tended to have more “gender atypical” features with a focus on how hormones or other biological factors affect orientation.

Sample Size & Methodology Confound Results

The sample size was around 35,000 facial images. When shown 5 images of the same person, the accuracy of the results increased to 91% and 83% respectively.

This result does expose a threat toward members of the LGBTQIA community. In a world concerned with invasive technology, those who wish to have their orientation remain anonymous could struggle. 

But there’s a deeper issue: reductivist categorization.

These same kinds of algorithms are also intended to divine which people are more likely to be pedophiles or criminals. Is such a thing possible or are we going to encounter a Minority Report situation where your potential brings practical, negative consequences?

Phys.org reports: “the methodology used followed common practice in this field of research, which is to treat any publicly accessible data as “fair game”, no matter that the data subjects likely never intended their data to get used for these research purposes.”

Whether the intent of the researchers or not, these attempts at AI machine learning predictive algorithms exposed biases of human creators.

What’s worse: they’re adopting them, too.

5. Textiles: 3D Print Your Clothes

We stream music and other media. Some of us gather our veggies from local gardens rather than big box grocery stores. To me, this means there is a resurgence of decentralized economic models.

Due to the proliferation of 3D printing technology, this decentralization is reaching the textile industry, too.

Not only can you 3D print your own NYFW collection (though you might never show it), you can also 3D print armor for cosplays. This has huge implications when it comes not only to the American manufacturing economy but the global one.

After all, many of us wear clothes made in China, Taiwan, Indonesia, or another country. Could 3D printing disrupt these multi-billion dollar industries?

What Does all of This add up to?

Medieval city planning. New antibiotics. Improved, less harmful pesticides. Unbiased neural networks. Hand-printed and molded N7 armor for my Commander Shepard cosplay.

(That last one might be a bit niche).

Regardless of the methods by which we reach these future changes, it means a shift in mentality and activities in everyday life as we’ve come to know them in the era of globalization.

For some, it might mean vindication for all of their hours spent in games like Banished, Age of Empires, or Cities Skylines. For others, it means improved health and quality of life. But for some, it could mean total disruption or dismantling of their way of life.

What are the benefits to moving toward seemingly outdated systems like decentralized economic structures? Does it matter than neural network absorb biases from their human creators?