Ever wonder what the gig economy is all about? What is the experience of drivers, interacting with restaurants, with traffic, with the AI-in-the-cloud, with customers?
My son recently turned to this service to make some cash prior to his upcoming trip. Wonder of wonders, he offered to let me come ride-along for a few hours on one of his outings.
Finally! a chance to see behind the velvet curtain! Is there a Wizard in Oz controlling things?
We spent about 4 hours together, including the dinner rush. What did I learn, as a parent and an informaticist?
Gas is expensive.
At $5, it eats (pun intended) into any profit margin. Food delivery is particularly hard right now, but I can’t imagine it is much easier or more lucrative even with less expensive gas.
This is hard work.
Even four hours is a lot of work. I can’t imagine doing this for longer, and day after day. My son, after a couple of weeks, notes “this could be an occasional supplement to someone with an existing job, but I can’t see doing this full time for the few dollars it brings in.”
It is good to go online…
And learn tricks from others. I haven’t done the surfing, but it sounds like there are YouTube videos for strategies on how Dashers can make money. For example, “don’t take every offer that comes to you over the phone.” Some deliveries only offer a couple dollars for 2-3 miles of driving, working out to about a dollar a mile. From what we believe of the algorithm, if a driver turns down a delivery, the next driver gets a slightly higher offer. IF that is the case, it is the responsibility of drivers to look out for each other and decline overly cheap delivery offers! (see: Fight the Man!).
The informaticist likes end users who educate themselves to improve their own workflow and experience.
Traffic is terrible.
And some drivers have lost sight of their humanity. I occasionally see bad behavior on the streets when I’m driving, but spending 4 hours driving around the city gives you a concentrated view of your neighbors. The pandemic has done something to our vehicular civility. People honking at folks driving the speed limit, people swerving and gunning their engines to get 1 or 2 spaces ahead in traffic, emotions running high while operating multi-ton vehicles. A dangerous workplace.
The informaticist understands strong emotion and unhappy end users who act out at times.
Sometimes little physical tweaks help provide better service.
Having an insulated shopping bag keeps the food hot a little longer on your drive from the source to the delivery. Wearing comfortable clothing, having a phone with charger (a task-horse! Receive delivery offers, map your drive, text your delivery recipient that you are on your way, take a photo to prove you left it in the right place), can help.
The informaticist enjoys seeing workflow tweaks that improve outcomes.
The smells are free, but it costs you.
One bad side effect of driving food around, is that the food smells eventually get to you. Maybe not when you start, but inevitably you’ll get hungry. Uh-oh. Those fries … fast food places sure have dialed in the sensory experience. Other times the food is not to your preference, and you can’t get there soon enough to let it go. On the other hand, you get to learn where people like to order from, and you’re likely to find some new places to eat (we found bb.q, a relatively new Korean barbecue chicken place in Denver!).
Don’t forget the drink(s)
The algorithm is smart enough to remind you to pick up drinks; having several moving parts to the order — not just the food bag, but also drink(s) and secondary items — complicates the process and increases risk of error, so some reminders are built in. Also, some restaurants are on the app and can also call you back if you miss something.
Error-anticipating and error-correcting. The informaticist smiles.
Don’t be greedy. Or maybe, be greedy.
Apparently, some gig economy workers run Door Dash and also Uber Eats and sometimes also Uber and Lyft at the same time, just to increase their chance of picking up more offers and staying busy. I can’t imagine the cognitive load (and increased danger) that entails, whether stationary or while moving.
Separately, the app will sometimes try to package deliveries together (hey! if you drive another block, you can deliver a second request from a nearby restaurant, want to?) I can see the algorithm trying to lower costs and combine trips within a restricted time-block and geography-block. Kind of like the ‘traveling salesman‘ math problem. Except different.
The informaticist likes the math, hates the multitasking.
The attention economy
This usually refers to advertising, social media, how they are all now optimized to capture your attention and keep it. See: Made to Stick, The Shallows, Reality is Broken. Also see: every social media app on your amazing phone.
In this case, how does the algorithm capture you? It tells you, “Hey, you’re not accepting enough of these offers.” The little joyful “ping” of a new offer keeps us on the edge of our seats waiting to see what pops up next. It is hard to quit driving at the time you set yourself. “I’ll just do one more, maybe the next one will be the big score!” Like Pavlov’s dogs, we could literally salivate when awaiting the next reward.
The informaticist likes “sticky” design, but only when used for the greater good.
Sometimes the little social tweaks can improve tips
My son learned to use the optional “send a message” tool. He would use it to tell the recipient that he had picked up the food and was on his way, with an ETA. “Hi Betty, Joe here. I’m on my way! ETA 10m.” He even worked out exactly how few letters it would take to send a friendly note, with his name included, hoping for a better tip. And it works, most of the time!
Informaticists like social engineering nudges when used for good.
Fight the man
Not all algorithms look out for the frontline worker. “Fight the man!” becomes “Fight the code!” It is disappointing that gig economy algorithms have no allegiance to their drivers. No “company loyalty” engendered here: it seems that the algorithm is testing “how low will you go?” Here’s an offer to pick up from McDonalds for $2 to drive 2 miles to deliver. Want it? (No). Or pick up from Applebee’s for $3 to drive 4 miles? (No). How about pickup from Korean fried chicken for $6 to drive 3 miles? (Yes).
Sometimes it isn’t busy, and you have to decide whether to take the lower paying deliveries because there is nothing else. But is that better or worse than parking and turning your engine off, saving gas, waiting for the next one?
Sure, the algorithm has to make money for its Master-in-the-sky, but surely we can take care of our frontline workers and set some sort of regional minimum wage? Deliveries at $2/mile are helpful, but when it is $1/mile, it works out to less than minimum wage, and recipients do not often tip.
Hmm. Can the informaticist learn from game theory to improve user engagement in our common purpose? And are there principles of respect for frontline workers in the design of artificial intelligence algorithms that make life better for all, not just the corporation?
Finally, be grateful when a son or daughter volunteers to let you come along to do something crazy like this. I’m aware these opportunities will not always be there.