Figure 2: Robot prices and labour compensation in manufacturing in the US (1990=100) 220 Labor costs 200 180 Source: Tilley, Jonathan, "Automation, 160 Robotics, and the Factory of the Future", 140 September 7, 2017, Mckinsey & Company. 120 100 80 60 40 Robot prices 1990 1995 2000 2005 2010 Now, consider Bruno, who owns a small manufacturing firm and produces windscreens for automobiles. Currently Bruno uses two robots and ten workers including Angela in his production.Figure 3: Fraction of offers rejected in the ultimatum game, according to offer size and the number of Responders 100 Fraction of offers rejected (%) One Responder Two Responders 75 50 25 0 0 5 10 15 20 25 30 35 40 45 50 Fraction of the pie offered by the Proposer to the Responder(s) (%)The red bars show the fraction of offers that are rejected when there is a single Responder. The blue bars show what happens with two Responders. When there is competition, Responders are less likely to reject low offers. Their behaviour is more similar to what we would expect of self-interested individuals concerned mostly about their own monetary payoffs. To explain this phenomenon to yourself, think about what happens when a Responder rejects a low offer. This means getting a zero payoff. Unlike the situation in which there is a sole Responder, the Responder in a competitive situation cannot be sure the Proposer will be punished, because the other Responder may accept the low offer (not everyone has the same norms about proposals, or is in the same state of need). Consequently, even fair-minded people will accept low oers to avoid having the worst of both worlds. Of course, the Proposers also know this, so they will make lower oers, which Responders still accept. Notice how a small change in the rules or the situation can have a big effect on the outcome. As in the public goods game where the addition of an option to punish free riders greatly increased the levels of contribution, changes in the rules of the game matter