The cognitive bias is referred to as the systematic discrepancy from the answer which is correct and is within the judgmental task, it is provided through the decision maker or formal normative rule or expert’s actual answer for such task. The motivational biases are the situations where the judgments are normally influenced through the undesirability or the desirability of outcomes, events, consequences or even choices. For instance, motivational biases can be said to be an attempt which is deliberate of an expert to offer an optimistic forecast for the expected outcome or even action. Another good example is the cost underestimation within the projects to have a bid which is more competitive. The motivational biases are not always conscious, like the case for the time estimate for particular software to be completed can be overly optimistic (Michalski, 2013). It happens even when there is no pressure from outside or any value from the misrepresenting the real time. De-biasing is referred to as the attempts to have the elimination or reduction of the motivational and cognitive biases.
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Anchoring is a type of cognitive bias where it happens when the estimate of the numerical value is related to the initial value which is referred to as the anchor; this is then not sufficiently adjusted to offer the final actual answer. Anchoring bias is evident in various areas like the estimation of the task and also pricing decision which is also within the negotiations. The de-biasing techniques for the anchoring biases are making sure that the decision maker avoids the anchors. It can also be minimized by making sure that one offers a many options and counter anchors. Anchoring biases can also be reduced by utilizing the various different experts who have to be also utilizing the different anchors (Modarres, 2016).
Availability is another bias also referred to as the ease of recall. It normally happens when there is a probability of the event which is possible to have an easy recall and also have been overstated. The bias is evident when there is a simple frequency estimate. It can be reduced by making sure that the decision maker has a probability education and training to make sure that he or she understands the process. It is also important to make sure that one has the counterexamples and also the provision of the statistics available (Kerzner and Kerzner, 2017).
Certainty effect is also another bias which affects the process of decision making and also the risk analysis. It happens when their people want to be sure of the things they want to gamble while utilizing the things that they are sure of. It also happens where people also want to have the discounting of the sure things in a dramatic way a time they are not sure. It is evident where there is the probability versus the certainty and the equivalent ways to offer different outcomes. It is possible to avoid or reduce sure things within the utility elicitation. It is also important to have the utility and value of elicitation. The decision maker should also ensure that there is more exploration of the relative risk of attitude parametrically (Velasquez and Hester, 2013).
Equalizing bias is another bias when having a decision making and also the risk analysis which happens when the person making the decision has the allocation of the similar weights to every objective. It also happens when the decision maker places the same probabilities for every event. The equalizing bias can be reduced or avoided by making sure that decision maker ranks the objectives and the events first before assigning the ratio weights. It is also possible to carry out the elicit probabilities and weights hierarchically (Kerzner and Kerzner, 2017).
The gain-loss is a bias which happens as the alternative details of choices and also its results whether it is a loss or a gain which may also lead to other answers. The gain-loss bias is evident when there are many areas entailing the choices of options which are risky in having the evaluating the single options within a particular attribute and also the manner in which the outcomes are outlined to have the promotion of the choice. It can be de-biased by making sure that the decision maker has identified the status quo, in case of the value functions, the expression values are the marginal changes as from the status quo. The utility functions are supposed to be eliciting utilities for the losses and also the gains separately (Velasquez and Hester, 2013).
The myopic problem representation is a bias which occurs while conducting the decision making or even the risk-taking where there is an oversimplified problem which is adopted in relation to a not complete mental model within a decision problem. The evidence of the bias is that it focuses towards the alternatives which are in small numbers; it also focuses towards the objectives in small numbers. The myopic problem representation bias can be reduced by making sure that the decision maker has more objectives, other alternatives and also other future possible states (Haimes, 2015).
The bias happens when there a very crucial variable has been overlooked, it is normally evident in the process of the objectives definition, alternative decision identification and also the generation of the hypothesis. The bias can be fully be avoided by making sure that the decision maker has the done more evaluation for more objectives and also the alternatives. It can also be reduced by using the techniques of group elicitation (Kerzner and Kerzner, 2017).
Overconfidence is a bias which happens in a situation where the decision maker may offer an estimate for a particular parameter which is above the expected performance. It is evident in the quantitative estimates like the legal, defense, engineering and legal decision. It is also evident in the judgments in relation to the hypothesis completeness. The overconfidence biases can be avoided by the utilization of the proper training of probability. It should also start with the presence of extreme estimates like high and low, and also strictly avoid the central tendencies anchors. It is also possible to reduce the biases through the utilization of the fixed value apart from elicitation of the fixed probabilities (Haimes, 2015).
The affect influenced is a motivational bias which happens when there is a situation of emotional predisposition against or for a particular result or even an option which taints the judgment. Research shows that the effect influences the probability of the events estimation. It can be de-biased by making sure that the decision maker avoids the description which is loaded within the attributes consequences. It is also possible to reduce the bias by making sure that one has cross-checked the judgments together with the protocols of alternative elicitation in the process of eliciting weights, value functions and also the probabilities. It is crucial to utilize the multiple experts to make sure there is the more alternative point of view which will help in the process of the minimizing or terminate the effect influenced biases (Kerzner and Kerzner, 2017).
Confirmation is a bias which happens in a situation where people have the strong desire to have the confirmation of the believe they have, this causes them to have an unconscious selectivity aspect in the process of absorbing and utilizing the evidence. It is evident in the process of information collection, task selection, evaluation of own-judgments and also the evidence updating. The biases also affect the real-world context like in the medical diagnostics, scientific thinking and also judicial reasoning. The confirmation biases can be de-biased by making sure that the decision maker utilizes more experts who will offer more opinions to help in the judgments (Larson and Gray, 2015).
The bias occurs where a person has more desire to have the outcome, this causes him or her to have more expectations of what will happen than what exactly can occur. The bias is evident when the estimation of the cost is made and also the estimation of the duration to be taken for a certain project. It is also commonly found at the sports results estimations. The biases can be reduced through the utilization of the decomposition and also the assessment of the realistic partial possibilities (Velasquez and Hester, 2013).
The biases happen when people have the desire to be conservative, prudent or cautious in the process of estimating the activities which might bring some harmful consequences. It is a bias that is extremely evident in the projects related to the risky technologies. It can be de-biased by the making sure that the decision maker has consulted so many experts in the same field before making any concrete decision (Kerzner and Kerzner, 2017).
The bias causes the underestimation or overestimation of the probabilities, values, weights or consequences in the ways that will only favor the alternative which is desired. The biases can be reduced by making sure that one has utilized the adequate or incentives for degrees of accountability (Hu et al., 2013).
The ambiguity aversion is a bias that is evident where people normally take the gambles with the explicit probabilities stated than the gambles which have unspecified probabilities. It is corrected by making sure that one quantify and model ambiguity as for the distribution of the probability. It is also corrected through modeling it like the uncertainty parametric (Haimes, 2015).
Base rate fallacy, it is a bias that occurs when people assume the base rate in the process of making the judgments for the probabilities and instead have the reliance towards the particular individuating information. It is corrected by making sure that one has the splitting of the task into base rate assessment.
The conjunction fallacy is another easy to correct biases which occur where the two events are normally judged like they are part of the one constituent event. It happens where the probability is judged is related to the reference case which is the same as the conjunction. It can be corrected through making sure that one has the access separately to the two events’ probability, and also make sure that there is an accessing of the conditions of one even probability while offered the other event (Clemen and Reilly, 2013).
Conservatism is another easy to correct biases which occur when people fail to revise effectively the probabilities provided. It can be corrected by decomposing the task provided in the estimation of the probabilities and the likelihood that are prior.
The endowment effect is a bias which can occur in situations like when people demand more payment of the properties they already own other than the things they might not own. It also occurs where people want to have a sunk cost when they are having the prospective decisions. It can be corrected by making sure that all the sunk cost is not included in the analysis. It can also be reduced by making sure that there is the showing of the asymmetry logic for the gains and losses. There should also be the convergence of the minimum prices of selling and the maximum prices of buying logically (Cardona, 2013).
It is evident from the discussion that there is difficulty when it comes to the decision making and risk analysis when the aspect of biases is considered. There needs to be a strategic way of making sure that all the decision makers have evaluated enough the aspect of biases since the cognitive and motivational biases have been seen to really influence the manner in which solutions are acquired. It is also important to differentiate between the biases which can be easily corrected and also once which are difficult. It is therefore upon the decision makers to take the initiative of making sure that they engage a lot with the techniques to reduce or finish the biases in their engagement, like incorporating a lot of opinions from various experts in their field.
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