Inside, a robot is mostly the same concept as any other computer-based design:
- It always requires an input with sensors that detect something that physically changes. This input is often a camera or microphone, and often includes sensors along with it. If it’s a simple-enough robot, it simply needs sensors.
- The operating system is relatively similar to any other computer, though interacting in the “real world” is absurdly complex compared to working strictly with raw information.
- The processor eventually operates an output that physically does something. It may use a screen, but almost always uses a mechanical arm, and typically has lots of driver “middleware” to accommodate the extra mechanical hardware.
Externally, though, a robot is the ultimate “implementation” of a computer in the physical world. All other computer aspects are mostly confined to the realm of the mind and ideas, but robots have the means to legitimately do things.
The first industrial robot was Unimate, created in the 1950s by George Devol. It worked on an assembly line at a New Jersey General Motors plant and worked off drum memory.
Uses
Most robot parts are designed by borrowing directly from nature or existing technology.
Robots are designed for various uses, based on the roboticist’s purposes. However, their uses are always far more limited than someone employed in a relatively similar capacity.
The tasks a robot does best are highly precise, highly repetitive, or require hair-trigger reaction times. One system for controlling them is called computer numerical control (CNC), which specifies with precise mathematical formulas where the computer should go and what trajectory it should travel.
However, robots are terrible at some tasks:
- The input information sometimes requires further investigation to determine if it’s worth acting on, but some inputs are too vague to articulate into logic.
- The output must be modulated according to an approximate estimation, but that estimate may be too vague to articulate into logic.
- Absolutely anything involving human interaction is a somewhat emotional experience, but more on that below.
Because of the excess of details and the very specific use cases of robotic machinery, the most prevalent use of robotics is in tedious factory and warehouse work. In fact, some warehouses are almost entirely automated. Even machine learning won’t change that.
Dumb Machines
In many respects, a robot demonstrates how utterly stupid computers are. They are effective at doing exactly what they’re told, repetitively, but don’t understand how to improvise or adapt.
One simple example of this idea is the seemingly easy task of laying bricks:
- Lay mortar.
- Place brick evenly on mortar.
- Lay mortar on the side.
- Scrape off excess mortar.
- Repeat.
However, after a few trial runs programming a brick-laying robot, you’ll notice it creating bad brickwork. Debugging would show details necessary for a successful task:
- If any bricks slide from their spot, put them back in their place or adjust other bricks.
- Press firmly on the mortar to create cohesion, but not so firmly that it offsets the brick from the others too far.
- If there are any offset bricks, place future bricks at an aesthetically similar height to reflect them.
- Recognize impurities in the mortar and compensate the brick for it.
All of this would be resolved by the intuition of just about anyone who has been laying bricks for a few weeks.
Computers are the world’s fastest idiots, and robots demonstrate it by understanding specificities without grasping anything in the realm of general principle or intuition.
As another example, imagine instructing someone to pick up pebbles from a flat surface and place them in a jar:
- Pick up the pebbles you see over there (pointing finger).
- Place the pebbles in that jar there (pointing finger).
- Inform me when you’re done.
While small children can do this easily, effectively programming a robot takes a lot of work:
- Demarcate the grabbing zone, indicated as a specific range mapped out from captured camera information.
- Set an algorithm that clarifies exactly what a pebble is, then create instructions to grab it, with each grabbing effort modulated with the camera data for every single pebble.
- Move the arm to the jar, which must be exactly specified before the maneuver. There should be subroutines for whether the jar is missing, full, fell over, or broke.
- Repeat 1-3 until all pebbles are in the jar, then clarify a stop sequence for the arm to rest.
Robot AI must also incorporate elements of kinesiology to manage complex tasks.
Less Dumb
One of the easiest workarounds for dumb robots is to have robots operated by people who remotely control them:
- When a location is too unsafe (e.g., near a bomb, drilling), remote-control robots have been popular for decades.
- Robotic hands and legs may soon become novel prosthetics technology for disabled people, assuming the artificial limb can accurately process nervous system signals.
Lately, machine learning algorithms have dramatically improved the variability of the robot’s instructions. They still have some trouble improvising while crossing difficult terrain, but can balance enough to ride skateboards or zip lines.
But, they’re still relatively useless when completely unsupervised, and are still dumb enough for an errant cardboard box to force them to stop.
The largest impediment to robotics advances, however, is in how absurdly difficult programming seemingly simple tasks becomes:
- The logic necessary to frame robotic instructions is conventional software design work.
- The input is very fuzzy, and almost always analog.
- The output typically must fulfill very precise specifications.
- It’s difficult to correctly account for all the “edge cases” you can’t know while programming a robot.
- Even after many iterations, the work to revise a robot’s code is never technically done.
Dozens or hundreds of hours of expert programming can often be offset by a simple stroke of intuition.
Fantasy
Beyond reality, robots have a tremendous draw in the world of fiction, and people like to imagine rather dramatic (and unrealistic) portrayals of what robots could do:
- All low-skill jobs replaced by robots, to the point that unions will fight their use in a workplace.
- Human-looking robots in customer service roles.
- Use cases in the sex industry.
However, beyond the above concepts about how dumb they are at tasks, there are specific problems for many of the perceived domains:
- In the event of a poorly programmed robot, high-risk robotic implementations (e.g., cars) won’t withstand human nature’s tendency to blame when people die, so it becomes a heavily politicized situation far more than simply upgraded technology.
- To make a human-like science fiction robot (e.g., Asimov’s “I, Robot”) would require adding the fields of psychology and sociology into all the other disciplines required for robots, meaning robots would have to first be ubiquitous everywhere to approach that challenge.
- Like realistic game development, widespread adoption of robots will always be suppressed by the uncanny valley:
- Robots are more relatable as they become more human-like, and they’re very relatable when they’re precisely human-like.
- Right before they’re fully relatable, there’s an odd point where their behaviors and mannerisms are terrifying and creepy.
- At that point, a robot sabotages all human connection it may have gained, and will create a prolonged state of unease for the observer.
In particular, the uncanny valley can deter the public at large, since they’re conditioned against it further through the genre of horror stories and spend more time among other humans than most roboticists. Human expressions are vastly complex, with precise timings and exceptions for absolutely everything, and robots simply can’t compete with the intuition required to accomplish something that could pass as human.
Economics
Like all other technology, robots have a more profound effect than people who discredit them believe, but that profound effect happens over longer periods than the apologists would be quick to assert.
Despite the sillier trends attributable to robotics, there have been changes to society:
- Robots have very specific, purposed uses in realms like horticulture, factory work, military support, and navigating small corridors. Many of them are remote-controlled, but they serve as an agent of the human who uses them. This arrangement has been completely favorable.
- Skills do get replaced, which frees up people to do other things. People find meaning in work, and they do something else that can add value, though older people surpassing about age 40 can be left behind from the change as the technology develops. This, however, happens slowly enough that it never destroys society in any collective sense.
- Lower-intelligence jobs (i.e., for people below an IQ of 85) have almost ceased to exist, since robots can do the job, and nobody has found a workable solution for this. It’s reasonable to expect the most intelligent people in society to solve this issue, but that’s not how the world works.