Tag Archives: artificial intelligence

Who are able to Keep Their Jobs when the Robot Apocalypse Happens?

terminator

Majority of the work we are doing as marketing professionals will be done by robots in (not so far) future. So if we won´t embrace that change, we will The workforce lead by robots is not only a threat for luddites but also opportunity for broad-minded professionals. Before anything can be automated and singularity kicks in, there will be a (probably relatively long) period of augmentation when we can work alongside with smart machines.

In their book ”Only Humans Need Apply”, writers Tom Davenport and Julia Kirby list five potential ways for us humans to remain relevant when robots starts to take over:

Step Up
Overseeing the automated systems.

Who will keep their jobs in advertising industry?
A few lucky managers, who are visionary and ruthless enough to replace majority of the workforce with automated systems.

Step In
Learning more about how robots will work and how to improve them.

Who will keep their jobs?
Those who are currently good at their jobs but not opposed to progress and using robots to do majority of the heavy lifting in their work. Combination of machine learning and human tacit knowledge is quite often the killer combination compared to only-human and only-robot approaches. At least for now.

Step Aside
Paradoxically the much-ridiculed ”soft skills” are more robot-prone than the more analytical skills. It is easier to teach robot to kick your ass on math challenge, but way harder to teach robot to have empathy when your colleague is having a bad day.  Using human skills like motivation, creativity, persuasion or empathy while using the automated systems will be the killer combination in expert services (e.g. financial advisory: robots are doing the investing, humans are doing the selling).

Who will keep their jobs?
Everyone who can sell and gets along with people. Evem when majority of the hard work is done by machines you still need human touch to sell those solutions to other humans.

Step Narrowly
Specialize in field so obscure that it does not make sense to automate.

Who will keep their jobs?
Those specialists who you call to perform really weird tasks with high price tag (e.g. the best taxidermy photographer, world´s best copywriter for sanitary pads, scouting agent specializing in New York) and you always wonder how they make their living (from those weird tasks and commissioning premium, duh). In global marketplace there is enough demand for pretty much anything and there is always higher demand for the best one in the field.

Step Forward
Developing new systems and technology to automate processes.

Who will keep their jobs?
Forward-looking people who have good understanding of current processes and preferably understanding of data & algorithms (or alternatively ability to speak the same language as data geeks).

As we can see from this list, there are plenty of opportunities in our field to work alongside smart machines. What combines all of these ways (maybe excluding stepping narrowly which is probably the least applicable route to majority of us) is that we need to embrace the improvements that smart machines can bring to our ways of working.  We need to be willing to work to add value to machines and be willing to let machines add value to our work. If you are opposing change and just hope for legislative restrictions to slow down the inevitable, you are without your job sooner than you think.

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Machines Will Eventually Beat Humans in Everything

“I don´t think it will be a close match. I believe it will be 5–0, or maybe 4–1. So the critical point for me will be to not lose one match.”
Lee Se-Dol (Korean Go champion before his matches against Alphago)

Lee-Se Dol was able to predict the future; it was just the opposite he was envisioning. Alphago (computer Go program done by Google subsidiary Deepmind) slaughtered him in six games.

alphago

Machines beating humans in a game is nothing new. In chess the gap between machines and human is already tremendous. Best chess machines are even able to win joint teams of human and computers. What makes AlphaGo´s victory intriguing is that Go is much more complicated game than chess. The first move of Go can involve 361 positions (chess has only 81) and Go game generally lasts more turns than chess.

Simple heuristics get most of what you need. For example, in chess and checkers the value of material dominates other pieces of knowledge — if I have a rook more than you in chess, then I am almost always winning. 
Go has no dominant heuristics. From the human’s point of view, the knowledge is pattern-based, complex, and hard to program. Until Alphago, no one had been able to build an effective evaluation function.”
-Jonathan Schaeffer (Creator of Chinook, first program to beat humans in Checkers)

The machine victory in Go happened decade earlier than experts predicted.

AlphaGo is based on deep learning and neural networks. So while Deep Blue beat Kasparov with sheer computing strength, Alphago has more artificial intelligence behind it. Firstly neural networks were trained on 30 million moves from games played by human experts. That resulted to ability to predict human move 57 percent of the time. But that gets you to the same level as human players not necessarily able to beat them. So secondly, AlphaGo played thousands of games between its neural networks, and adjusting connections using trial-and-error process through reinforcement learning.

How many humans are even able to comprehend what above means (lest train themselves in even somewhat similar manner)?

Machines can already replace humans in more fields than we are willing to admit. And more importantly, they are playing better job as well. Machines can crunch data to obtain experience, which is impossible for humans during their lifetime. We have to start embracing machine learning and collaborating with machines more if we want to survive. Advertising industry has been especially almost hostile to any technological improvement. That will be a road to sure destruction. Beating a Go champion is much harder task than to do a subpar brand campaign. If we don´t take more proactive and positive approach to data and artificial intelligence, we will make ourselves redundant.

Machines can either be our allies our friends. I would opt for the latter choice.

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