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Let's imagine you have ten people from various walks of life isolated in a large room. The room includes food, drinks, and everything needed to make the experience pleasant and comfortable. The people all know each other somewhat and some are even friends. You walk into the room and ask the group a complex question in some technical topic. Fortunately, some of the members of the group are experts in the topic while some of the others have college degrees in other fields. The group deliberates on the question. After a variable amount of time, the group reaches a consensus and gives you an answer. How confident would you be that the answer given is accurate? Would you risk your health or your life on it? Would you risk the life of a loved one on it? Would you risk the environment or society's quality of life on it? Whether you like it or not, you already are.
This hypothetical is consistent with the model used for making important decisions everyday by very important people in our society. Congress amounts to a very large group of men and women sitting in a large room, deliberating issues to reach a consensus. Board meetings at corporations, non-profit organizations, and even special interest groups follow similar models. Democracy, itself, is an abstraction of the model I have described.
So what's wrong with making decisions this way? The problem is that this model does nothing to minimize the potential for a collective bias. Biases are, most often, personal and, thus, reflect personal values, individual world views, subjective positions on issues, and other things. As people interact with one another in a group over a long period of time, overlaps in the personal biases of a group's members eventually become the collective bias of the group itself.
For example, if you walked into a vegetarian conference and asked the group a question about healthy eating, the probability of getting an answer involving the word "meat" is nearly zero. Even if there was someone within the vegetarians willing to suggest a meaty dish, he or she would not contribute this recommendation for a fear of social pressure in such a highly accessible situation. I am not suggesting that vegans have anything to hide, but I am attempting to illustrate why strong overlaps in personal biases can become a collective bias with a penalty for those of the in-group who disagree. When people speak of conspiracies theories in business and government, they are directly referring to the presence of a collective bias which forms a component in the group's method for determining facts and making decisions.
What are the qualities forming the basis of a collective bias? First, the members of the group must be accountable to each other in one way or another. The group must have a collective goal in mind with a penalty for those in the group who either do not cooperate or attempt to interfere. Secondly, and most pressingly, the members of the group must be accessible to each other. If members are not accessible, they are immune to social pressures and there is no means to impose a penalty for dissidence. They are effectively beyond persuasion or the transmission of personal bias from others in the group.
In truth, government and business pick the worst possible avenue for making decisions, leaving them highly vulnerable to collective bias, yet we trust them with our lives and well-being everyday.
The Scientific Way
Let's try our hypothetical again. This time, we'll use a more scientific model to minimize the likelihood of a collective bias emerging. We have a complicated question in the field of biology that we want answered. We gather ten experts from various countries, various age groups, various employment statuses, and other degrees of variation so as to minimize the overlap of cultural and personal bias. We isolate the experts in ten sealed rooms. The rooms are comfortable, but the experts have no means of contact nor any awareness of each other.
You enter the first room and ask Expert #1 the biology question. After some time to deliberate, he gives his answer and provides his reasoning and evidence. You leave the room and to go Expert #2. You ask him the same question. Expert #2 provides a very different avenue of reasoning with only some overlap with Expert #1, but provides the same conclusion and similar evidence. Expert #3 does the same, providing the same conclusion with comparable, but different, reasoning. So far, we can infer with reasonable confidence that the overlapping information we are receiving from the experts is factual as they were reached independently with no chance of any bias diluting the result.
You continue this pattern all the way up to Expert #10. You are surprised when Expert #10 delivers a completely contradictory conclusion than his nine colleagues in the other rooms. He has evidence to support his conclusion as well as compelling reasoning. Despite this, we have a very strong consensus in favor of the conclusion given by Experts 1 through 9.
So how do we deal with Expert #10? Do we ignore him as an anomaly? Of course not. He could be right! We take his evidence and reasoning back to Experts 1 through 9 and see if they can resolve the disagreement with further evidence. Once again, independent inquiry with Experts 1 through 9 delivers comparable rebuttals for Expert #10 with some variation in their reasoning, all providing evidence along the way. We return to Expert #10 and provide an extrapolation of the rebuttals. Expert #10 responds, "I don't know who you are talking to, but they lied to you."
What an astounding response! How could that be possible? They all delivered the same conclusion with nine different avenues of reasoning, even overlapping in some key areas. The experts were inaccessible to each other, so they could not have agreed to a conclusion ahead of time. The experts were not even aware of each other and, therefore, had no accountability or means of penalizing or transmitting a bias.
You have revealed a strong personal bias in Expert #10. Still, he has failed to stop you from reaching a consensus. The conclusions delivered independently by Experts 1 through 9 are most probably accurate. In science, this is known as a "concordance." This is how science works. We can never rid ourselves of personal biases, no matter how hard we try. We can, however, form a scientific community where no person's personal bias has the opportunity to speak for the group. Therefore, the scientific output is more likely to be factual.
I know what you're probably thinking. "But scientists are not completely inaccessible to each other." When new research is being contributed, they most certainly are. If you're an expert with a manuscript to submit to peer review, the editors at the journal will remove your name and contact information from the manuscript before sending it to a group of reviewers. Neither the submitter nor the reviewers are aware of each other and, thus, are inaccessible while the manuscript is being reviewed. If the reviewers are compelled by the contribution of knowledge in the manuscript, they recommend the paper for publishing and it is added to the journal for the scientific community to read.
So what about accountability? The scientific community is global in nature. We have scientists in every country. They work for a variety of employers. They come from various walks of life. They are, in no way, accountable to each other for anything. Even if the community rejects a given individual, a scientist can work perfectly well entirely isolated from his peers and never publish a single paper. In addition, it is worth noting that experts who review papers for journals may even be retired scientists who have nothing to lose or anyone to fear.
One of the arguments I often hear against science is that, "Scientists have to cater to business/government if they want grant money." I won't deny that some do, but what good would that be? If I falsified information in my manuscript to placate my employer, I would only be rejected from peer review by my peers who don't care if I get grant money or not. I certainly can't bribe them if I don't know who they are. They certainly can't prompt me for a potential bribe, because they don't know who I am either. We are completely inaccessible.
Cheating in Science
Let's say I just got a job working for Monsanto. I am writing a paper needed to gain credibility with the FDA for a new food product. My boss strolls in and tells me that I'll get a big raise if I'll make the paper more compelling, even if I have to adjust my numbers a little. If I don't, I risk being fired when the food product gets rejected by the FDA. Having no choice, I adjust the numbers and submit the manuscript to peer review. The journal sends my manuscript to a dozen reviewers in various locations around the world. Some of the reviewers are skeptical and attempt the experiment themselves, finding that they are unable to repeat by result. They send the manuscript back to the journal, recommending I repeat the experiment again and locate why my numbers do not work. I may have cheated because of the profit motive, but it just doesn't work in science.
Does that mean there is no way to cheat? Of course not. Let's say I have a colleague who works across the country who I am aware will almost certainly reject my paper if he is chosen as one of my reviewers. All I would have to do is call him up with a simple question for my research and acknowledge him in my citations. This will disqualify him as a potential reviewer. Will this give me any direct control or an avenue to slip in bad data? Fortunately, it does not.
If your presupposition is that government and business cannot be trusted due to a strong likelihood of a collective bias or incentive to falsify information, I have little basis to argue this point with so much evidence in history to show this notion factual. However, we cannot paint the scientific establishment with the same broad brush as it doesn't operate in the same manner. Science is not 100% without its own bias, but it is the single greatest way of determining fact with no rival even coming close. Science is not government and it is not business. Science is a barrier to block bias.
This blog is an editorial and contains only the opinions of the author. The author claims no expertise on most topics of discussion and this blog is not to be cited as an alternative for properly vetted journalism or scientific sources.comments powered by Disqus