From Saddle Making to Why We Shouldn’t Fear the Rise of the Machines

Scaling Human Effort using Machines

Examples of scaling are commonly found in our lives today, and is present whenever there is a hierarchy. In companies, the boss makes a decision, and his crew executes his plan. In the entertainment world, the efforts of actors and actresses are broadcast in cinemas and via Internet streaming reaching a large audience. In the software world, a program written by an engineer can be run on hundreds of thousands of servers in data-centers around the world with a click of a button.

Examples of scaling resulting from hierarchies

If we decide not to fear machines, but utilize them to our benefit, what’s next?

Two relevant questions at this stage are: how do we determine if a task should be done by us instead of machines, and what sort of skills do we need?

Specialization & Instruction

The typical answer to the first question is the level of creativity associated with a task. To invent a new game, we need a human. Machines can beat the best human chess players, but they cannot invent a new board game. On the other hand, machines are more suited to repetitive tasks that require precision. Even Foxconn, the manufacturer of our iPhones, is actively automating their factories. This assignment of specific tasks to different entities is not new: specialization improves overall efficiency and productivity in our society today, it is why we have farmers, teachers, plumbers, computer scientists, chefs etc.

The Human-Machine Communication Barrier

But, there’s a lot of effort today to get machines to even understand what we’re saying. In the last episode of this season’s The Grand Tour, Clarkson’s voice message to May was converted into a hilarious written version by his car. We keep trying, and trying, to get machines to understand human language, when they clearly aren’t very good at it. Or get good at it only after we’ve thrown massive amounts of resources into solving the problem. Would it be a more efficient use of resources for us to understand the machines instead, which requires training in programming languages? Or perhaps it is more likely that some sort of middle ground between human and machine language would be more appropriate?

For Silicon Valley Fans

Let’s all try and ‘make the world a better place’, via task-based hierarchical structuring of humans and machines, and realization of efficient and effective human-machine communication protocols.



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