Behaviors in the lab are different from behaviors in vivo in the real world.  This is especially true, for instance, in financial economic decision-making.  In classical financial decision theory, assets have an intrinsic price based on its future cash flows.  Discounting back to the present day provides an absolutely certain quantifiable and objective value and price.  Correct prices differ from incorrect prices as clearly as night and day.  Except there is one inconvenient fact immortalized by John Maynard Keynes - "...the market can remain irrational for longer than you or I can remain solvent."  In real markets, if everyone else is wrong, it means only you are.

Behavioral economics provides a patch to classical utility maximization theory.  They explicitly include modulatory emotions that warp the expected utility curve to suit an individual's perspective prospects, as in Prospect Theory.  By using a non-linear curve and emotional based theories such as loss aversion, they can model potential gains differently from potential losses more like a human would perceive them and less like an economic automaton might.  It can describe realistic behavior that results in suboptimal pure performance.  But what does it mean? Prospect Theory and Behavioral Economics as summarized in the Chartered Financial Analyst program cover the empirical phenomenon but (wisely perhaps) leave out the mechanism. It is merely something to either guard against or to exploit in others.

Combining these research findings with artificial intelligence or computer engineering - as would be appropriate, say, to create a script, an objective decision process, or even a semi-autonomous decision support system - would again lead to a disavowal of the emotional bias phenomenons. Engineers can build the Prospect Theory biases in if desired, but who wants a decision maker or decision making aid beset by a pique of greed or fear or jealousy? Again, this combination leads to a disavowal of the phenomenon, more as something that afflicts the other party and therefore creates an opportunity for the pure, unbiased autumaton performer.

Combining these research findings with neuroscience, as is occuring more frequently in the past decade, identifies the amgydala and insula as the neural correlates of Prospect Theory and emotional biases. Subjects with these areas intact see them activate when presented with choices and making decisions consistent with Prospect Theory predictions. Subjects with these areas otherwise deactivated depart from Prospect Theory and decide more similarly to Utility Theory. This evidence supports the intuitive claim that the emotional centers are involved when emotions bias decision-making. But what does it mean?

The amgydala and insula are parts of the limbic system, or the "old" and "reptilian" portions of the brain. Have humans perhaps evolved past the need for such components? Are these "old" and perhaps obsolete portions holding human decision making back from its pure capability? Should decision makers have these parts at least temporarily deactivated for their work? Would this be ethical, as doping and athletic performance enhancers for sports stars are unethical and illegal?

Perhaps to answer these questions one must be less wise and go beyond describing the phenomenon and attempt to explain the mechanism.