You’re killing time by doom-scrolling, as most of us do. Though we know that increased phone usage is linked with anxiety, depression and sedentary behaviors, it’s a compulsion that keeps us calm; it keeps our fingers moving and our brains active. In a more hopeful scenario, perhaps you’re ticking away the minutes between the bus’s arrival with a cute video about puppies, or a TikTok about communism that describes a low-fat way to eat the rich. Regardless of how you decide to spend your time on the glowing black mirror in your hand, at some point or another, you’re likely to come across a page that refuses to function the way you know it should.

We know the Twitter homepage like the back of our hand, after all–over ¼ of adults in the US use Twitter. We know that images aren’t supposed to just be empty boxes, that the ever-spinning circle beneath the bird logo is meant to lead to something. But, sometimes, it just doesn’t.

Why is that?

When it comes to data, simply put, there’s often not enough room on the surface of our cell towers for those who demand space.

This is where power amplifiers come in, small devices that offer more power-per-square-inch. These amplifiers, often in the form of CMOS, LDMOS, and silicon transistors, boost the radio frequency power.

If we have these devices, you might be wondering, why can’t we do this forever? Why can’t we boost and boost until everyone gets their daily dose of Facebook News? Because transistors have a maximum frequency (Fmax), an upper-boundary which cannot be crossed without causing damage and deterioration. Even before reaching this, transistors are known to operate within an efficiency region where we see their signal amplification abilities at their peak. Beyond this, difference between a resistor operating at 10VCE and resistor operating at 11VCE is nominal at best.

Looking at this in terms of broadcasting and the amplification of signals, the reason why we can’t simply increase the amount of bandwidth sent to our devices is because at a certain point, the amplification ability of the transistors responsible to said bandwidth simply plateaus, wherein adding more juice to our signals really won’t make much of a difference.

Another proposed way to combat slowing speeds and dead zones is to pump data to phones by the THz (terahertz) rather than the GHz (gigahertz) that we’re used to. THz, as the name implies, describes a unit of frequency defined as one trillion cycles per second.

That might not mean much on its own, so lets examine what a single ‘hertz’ is.

Like bikes, trikes, and the circle of life, energy moves in cycles. These cycles are typically graphed as a wavering line moving up, down, and back up again, what some people might recall from high school calculus as a sine wave.

With this in mind, we can understand that 1Hz amount to one full cycle in which a wave returns to its starting point of zero. 1Hz amounts to one cycle per sec, 10Hz amounts to 10Hz, and so on. Meaning that once we reach THz territory, we’re looking at technology that has the power to oscillate sine waves by the trillions each second. For this, however, we’re going to need to find ways to transmit lots of gain (which our current transistors aren’t meant to do), with lots of power and lots of efficiency, otherwise there’s a strong chance that even less of the transmitted signal will reach its target—your phone, in this case— and result in even more errors. To fix this, we need to design infrastructure meant to for heavy-duty tasks and heavy-duty signals, something that our current devices simply aren’t ready for. “The amplifiers designed at THz frequency range should be able to exhibit high performance at center frequencies beyond 100 GHz frequency range, while covering 20-30% fractional bandwidth,” writes Heydari.

By comparison, the fastest 5G cell phone currently on the market runs upwards of 29–39 GHz, which is still only ⅓ of what the spaces this technology is expected to explore in the coming years.

While several key performance parameters including the bandwidth, communication range, and frequency still remain a challenge, solutions are on the way and, soon enough, nothing will stop you from binge-watching Moon Knight during your next big commute.

All created in InDesign for a visual communcications undergrad class.

A short game written in Twine. Using concepts learned in class, I focused on social media and the 'watched watcher' within this narrative.

Full game here.

I am Read More Content.

AMERICAN AWARENESS AND CLOSED DOOR CULTURE HARRISBURG, Pa. -- An even six-feet and composed of few words ■■■■■ ■■■■■■, 23, considers himself to be the embodiment of suburban America, and he doesn’t think that’s a bad thing.

He enjoys skate culture from a distance, reads Men’s Health and strums guitar with the back of his thumb.

“I’m pretty odd with the stuff I do,” he said while adjusting his wireframe glasses.

When it comes to news writing, ■■■■■ believes there’s “no poetic element to it.” Instead, he prefers the freedom and individuality that comes from magazine writing.

He has a dopey smiley face, Nirvana’s calling card, etched into the right half of his rib cage.

The fading stickers taped to the back of his Macbook show SpitFire, Primitive and “Thrasher, obviously.” No prideful skate fan with be caught without Thrasher, after all.

When it comes to politics, ■■■■■ takes a back seat. “I would obviously be more liberal,” he said. “It’s kind of hard to a Republican if you’re not rich or a redneck.”

Beneath the surface of postmodern Americana, ■■■■■ expresses an Atlantic depth. Like writers Jack Kerouac, Charles Bukowski and Alexandre Dumas before him, ■■■■■ desires to keep the past where it belongs: behind him.

“I don’t like going back to my writing. I like to write it. I like to make it look good. And then I’m done with it. Especially poetry,” he said. “I don’t like to revise poetry.”

“He’s underselling himself,” his professor, Beth Kaszuba, said, implying there’s more to Shaffner than meets the eye.

‘Cobots' — An Examination

In recent years, collaborative robots — also known as ‘cobots’— have revolutionized the workplace and pushed us into a what has been colloquially known as ‘Industrial 4.0,’ a phrase which describes the “the next generation of manufacturing [which] advocates the increased use of sensors, information and communication technologies” (Weiss, 2). Naturally, an image of the future which advocates for harmonious interactions between humans and machines is not without its pushbacks. In Weiss, Wortmeier, and Kubicek’s essay Cobots in Industry 4.0: A Roadmap for Future Practice Studies on Human–Robot Collaboration, the ethical repercussions of human-computer interaction are discussed along with an examination of the robots currently seen in industry. Through their argument, readers can come to their own conclusion in regards to the current place of ‘cobots’ in the workplace. To this, Weiss and their team set out to share the current concerns with regards to cobots. Beyond this, they assess the parameters by which cobots are assessed, and make a call for the logistics of these terms.

To start, Weiss, Wortmeier, and Kubicek define collaborative robots as a modern solution to age-old problems seen in the industry. They make a distinction between automation and collaboration, claiming that automation is the delegation of functions from a human to a machine, while collaboration robots are specifically programmed to to work, interact, and collaborate with humans (2). Other texts support this definition. Kadir, Broberg, and Conceição define cobots similarly in their 2018 essay Designing Human-Robot Collaborations In Industry 4.0: Explorative Case Studies. In this piece, Kadir — perhaps more liberally — describes human-robot collaboration as “a new generation of robots are that born free and unbounded by any type of fencing or enclosure, transcending the boundaries and workspace limitations that prevented their ancestors (standard industrial robots) from cohabitating and working side by side with their human counterparts” (Kadir, 601). This assessment, as colorful and utopian as it may be, does little to recognize the inherent concerns most apply to cobots. According to Weiss, chief among these concerns are safety, trust, programming, the allocation of responsibilities, acceptance by humans.

With these concerns clearly laid out for us, Weiss goes on to explain in detail why these problems are for cobots. Safety, for example, is described in these terms: typical research questions explore [...] how safe operations can be maintained and how to avoid putting the human operator in the shared workspace at risk. This, of course, is a large component to all workplace environments. The safety of employees must be placed above all else, something that separates Industry 4.0 from revolutions of the past. Previously, as we expanded upwards and outwards into new industrial territories, we held little regard for those who made our growth possible. In the past, working conditions were difficult and exposed employees to many risks and dangers, including cramped work areas with poor ventilation, trauma from machinery, toxic exposures to heavy metals, dust, and solvents [Boston University School of Public Health]. Contrasting this, modern machinery is designed with the safety of its operators placed in the forefront. Weiss believes that, while a great deal of emphasis is placed on machines’ efficiency, the safety should be ranked as the most important factor when developing collaborative machines. “We argue that future research on safety and situation awareness in human–robot collaboration should not only focus on optimizing performance but also on whether the operator actually feels safe and whether situation awareness is given from an operator-centered perspective.”

Additionally, Weiss highlights aspects of automation which we’ve discussed in class. The four d’s — dirty, dangerous, demeaning, difficult — are areas where machines have commonly been used, but Weiss argues that these should not be the only places where cobots can/should be applied. “The ability to work around humans leads to the narrative that cobots can perform tedious, difficult, or dangerous operations[ …] but they enable higher level collaboration, including dynamic communication, optimization, learning, and program adjustments. Empirical evidence indicates that, in Industry 4.0, manual and mental routine activities seem to be replaced, while analytical interactive work is becoming increasingly important” (3 - 4). To this end, Weiss advocates for greater research into what it is that machines can do beyond repetitive, ‘dirty’ tasks.

Finally, and perhaps the component most prevalent in the public consciousness, is the concept of trust. For decades, the narrative has been that machines will steal jobs and place lower class people in further poverty. Rather than dismiss this claim, Weiss once again advocates for research and compassion, saying “we need broader stakeholder involvement when studying the actual impact of cobots on the future of work in Industry 4.0” [4]. In an instance that I have not seen before, Weiss considers cases where the trust between the cobot and the operator has been broken, and how this trust can potentially be mended. Examples of ‘broken trust’ include injury, error, unreliability, and faulty behavior (4). Instances where machines have performed poorly, how can we expect workers to continue to trust in the inherent goodness of cobots when they have been proven right? Weiss’s answer to this? “Trustworthiness should not only be studied as a robot-related factor but needs to be understood as the default situation between the human and the cobot” (4).

Now that Weiss has explained the issues facing machines, they go on to explain how current research into these issues is lacking. “The issue of (un)controllability in sociotechnical systems,” they argue, “leads to responsibility dilemmas culminating in an ethical debate about automatization and robotization of work.” Given the proper settings and the proper space to examine machines, these debates can be avoided. Even the best-designed interaction paradigm for a cobot cannot cover all possible incidents, as autonomous robot behavior will always include unpredictable consequences (5).

There is a disconnect, according to Weiss, between the machine and the profiters. This disconnect is illustrated within figure two, where the five components of the industrial complex are shown to have vastly different objectives and ways in which they’d like to approach those objectives. To conduct a meaningful study on human–robot work in Industry 4.0, it is necessary to consider different human and nonhuman actors, both in dyadic and larger constellations [7]. This brings Weiss and their team to their conclusion: research into collaborative robots should focus on several things at several different levels. It is not enough to only consider the concerns of the financial stakeholders, as it is not enough to consider the workers alone without giving consideration to profit margins and capital investment. Both of these goals must be studied in tandem within the context of interaction, use cases, and structural impact [7].

The narrative of cobots enabling safe, intuitive, and flexible interactions [...] sounds very promising, especially for small and medium-sized enterprises (SMEs). However, as our article shows, automation in the form of cobots has currently only found its way into the world of work in limited applications [9].

Works Consulted A. Weiss, A. -K. Wortmeier and B. Kubicek, "Cobots in Industry 4.0: A Roadmap for Future Practice Studies on Human–Robot Collaboration," in IEEE Transactions on Human-Machine Systems, vol. 51, no. 4, pp. 335-345, Aug. 2021, doi: 10.1109/THMS.2021.3092684.
Kadir, Bzhwen & Broberg, Ole & Conceição, Carolina. (2018). Designing human-robot collaborations in Industry 4.0 - explorative case studies. 10.21278/idc.2018.0319. “The Evolution of Epidemiologic Thinking.” The Industrial Revolution, https://sphweb.bumc.bu.edu/otlt/mph-modules/ep/ep713_history/ep713_history4.html#:~:text=Working%20conditions%20were%20difficult%20and,metals%2C%20dust%2C%20and%20solvents.