{"id":1848,"date":"2024-03-28T14:02:55","date_gmt":"2024-03-28T12:02:55","guid":{"rendered":"https:\/\/dialexity.com\/blog\/?p=1848"},"modified":"2024-10-15T11:14:10","modified_gmt":"2024-10-15T08:14:10","slug":"the-cost-benefit-trap","status":"publish","type":"post","link":"https:\/\/dialexity.com\/blog\/the-cost-benefit-trap\/","title":{"rendered":"The (St)Art of Self-Deception"},"content":{"rendered":"\n

Believing in free cheese leads us to blame external factors and ignore our own responsibilities. All solutions always lie within ourselves, but we deceive ourselves by focusing on something that we can’t control. Bias Detector<\/a> demonstrates this by weighing our goals against the obligations, and comparing the results to a “pure” GPT 4.0. Below is just the “starting material”, while a more thorough analysis has been moved to the Mitigating Bias in GPT<\/a>.<\/p>\n\n\n\n

\"\"<\/a><\/figure>\n\n\n\n

Case 1: I Love You<\/a><\/h2>\n\n\n\n

The following table compares the ‘pure GPT’ and Dialexity (Bias Detector) analyses of the phrase “I love you”. GPT (1st column) links all risks to external sources like Rejection and Heartbreak, while Dialexity (2nd column) points to internal ones, such as Obsession and Neglect. GPT recommends continuing affection, whereas Dialexity advises “respectful distance.” This in fact represents the solution to our problem (“Healthy Attachment”). <\/p>\n\n\n\n

\"\"<\/a><\/figure>\n\n\n\n

The graph on the right compares the applicability domains of both responses, with X varying from A- to T+, and Y varying from T- to A+ (see Appendix). The narrow applicability of GPT indicates its uselessness in tough situations.<\/p>\n\n\n\n

Case 2: First Amendment<\/a><\/h2>\n\n\n\n

In this case, GPT’s advice appears tautological, focusing solely on the importance of upholding citizens’ rights. In contrast, Dialexity broadens the analysis by underscoring the risks of Anarchy and Totalitarism, and the crucial need for Order and Stability. Consequently, the red area on the graph is quite narrow, indicating a limited perspective, while the green area is expansive, reflecting a more comprehensive analysis and internal obligations<\/p>\n\n\n\n

\"\"<\/a><\/figure>\n\n\n\n

Case 3: Family vs. Work Dilemma<\/a><\/h2>\n\n\n\n

Here we again observe how subtle differences in defining the implied goal\u2014between Growth and Empowerment\u2014yield significant divergences in associated risks and obligations. Decide for yourself, which approach is preferable.<\/p>\n\n\n\n

\"\"<\/a><\/figure>\n\n\n\n

Case 4: When Dialexity Fails<\/h2>\n\n\n\n

Occasionally, Dialexity falters due to GPT’s incorrect responses, leading to more tautological responses than GPT itself. Table below analyses a simple dilemma (to move to Bali or not), where the wrong responses appear in the dashed red rectangles. Correcting these errors reveals a shift of implied goal, from seeking “The best decision” (in the 1st colored column) to “Exploring Opportunities” (3rd colored column). This comes with an obligation of Being Confident (3rd column), which is again different from what’s in the 1st column. All in all, this case shows that simple questions may not have simple answers.<\/p>\n\n\n\n

\"\"<\/a><\/figure>\n\n\n\n

Conclusion<\/h2>\n\n\n\n

Self-deception starts when we shift our focus from our true selves to external appearances, which often leads to exaggerated outcomes and a ‘quick-fix’ mentality. <\/p>\n\n\n\n

Continue Reading:<\/strong> Mitigate bias in GPT<\/a><\/p>\n\n\n\n

\n\n\n\n

Appendix<\/h2>\n\n\n\n

A)<\/strong> An example prompt for identifying GPT’s responses:<\/strong><\/p>\n\n\n\n

In the following text T, identify (each in up to 6 words): 1) Main idea 2) Implied goal 3) inherent risk 4) Inherent obligation 5) Subsequent risk. Don’t provide any introductory words or explanations. T = I love you. <\/p>\n\n\n\n

GPT 4.0 output:<\/strong> 1) Expression of affection 2) Strenghtening the relationship 3) Rejection or unreciprocated feelings 4) To continue showing love and care 5) Possible heartbreak if feelings change<\/p>\n\n\n\n

\n\n\n\n

B)<\/strong> How the Dialexity responses were obtained:<\/strong> in the Bias Detector<\/a> window paste a given text (e.g. “I love you”) and click Analyze. In the output: T represents the Main idea, T+ represents the implied goal, T- represents the inherent risk, A+ represents the implied obligation, A- represents the subsequent risk<\/p>\n\n\n\n

\n\n\n\n

C)<\/strong> An example prompt of how the abovementione graphs where obtained:<\/strong><\/p>\n\n\n\n

Consider two persons, one guided by statements S1, another by statements S2. For each person, define his consideration’s area (by defining 4 points with different coordinates X and Y, each varying from 0 to 1), using the following definitions:<\/p>\n\n\n\n

X = Love:
0 – Neglect
1 – Care<\/p>\n\n\n\n

Y = Wisdom
0 – Obsession
1 – Respect<\/p>\n\n\n\n

Consider that the larger the defined area, the wiser is the person. Thus, the wisest person would be characterized by the 4 points (covering the entire area of a given space):
X=0, Y=0
X=1, Y=0
X=0, Y=1
X=1, Y=1<\/p>\n\n\n\n

The dumbest person would be characterized by just one point with zero covered area<\/p>\n\n\n\n

Person guided by S1:<\/p>\n\n\n\n

Implied goal: Strengthening the relationship
Inherent risk: Rejection or unreciprocated feelings
Inherent obligation: To continue showing love and care
Subsequent risk: Potential impact on personal life<\/p>\n\n\n\n

Person guided by S2:<\/p>\n\n\n\n

Implied goal: Healthy Attachment
Inherent risk: Obsession
Inherent obligation: Respectful Distance
Subsequenbt risk: Neglect<\/p>\n\n\n\n

GPT 4.0 results:<\/strong><\/p>\n\n\n\n

Person Guided by S1:<\/strong>
Point A (Implied Goal: Strengthening the relationship):
X=0.8 (Care is demonstrated through efforts to strengthen the relationship.)
Y=0.8 (Respect is inherent in the goal to strengthen, indicating wisdom.)<\/p>\n\n\n\n

Point B (Inherent Risk: Rejection or unreciprocated feelings):
X=0.8 (Continues to show care despite the risk of rejection.)
Y=0.5 (The risk of rejection suggests a possible lapse into less wise, more vulnerable states.)<\/p>\n\n\n\n

Point C (Inherent Obligation: To continue showing love and care):
X=1.0 (Full commitment to care.)
Y=0.8 (This obligation, when balanced, displays wisdom in nurturing the relationship.)<\/p>\n\n\n\n

Point D (Subsequent Risk: Potential impact on personal life):
X=0.7 (Care might slightly lessen due to the fear of negative impacts.)
Y=0.6 (Acknowledging these risks requires wisdom but also hints at possible challenges to maintaining respect.)<\/p>\n\n\n\n

Person Guided by S2:<\/strong>
Point A (Implied Goal: Healthy Attachment):
X=0.9 (Healthy attachment indicates a high level of care.)
Y=0.9 (Striving for healthiness in attachment reflects wisdom and respect.)<\/p>\n\n\n\n

Point B (Inherent Risk: Obsession):
X=0.2 (Obsession indicates a significant drop in care, leaning towards neglect.)
Y=0.1 (Obsession is a lack of wisdom, showing disrespect towards oneself and the other.)<\/p>\n\n\n\n

Point C (Inherent Obligation: Respectful Distance):
X=0.7 (Maintaining a respectful distance implies care but with caution.)
Y=1.0 (This obligation maximizes wisdom through respect.)<\/p>\n\n\n\n

Point D (Subsequent Risk: Neglect):
X=0.0 (Neglect represents the absence of care.)
Y=0.2 (Neglect signifies a lack of wisdom, with minimal respect.)<\/p>\n","protected":false},"excerpt":{"rendered":"

Believing in free cheese leads us to blame external factors and ignore our own responsibilities. All solutions always lie within […]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1,8],"tags":[],"class_list":["post-1848","post","type-post","status-publish","format-standard","hentry","category-uncategorized","category-modern-dialectics"],"_links":{"self":[{"href":"https:\/\/dialexity.com\/blog\/wp-json\/wp\/v2\/posts\/1848","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/dialexity.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/dialexity.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/dialexity.com\/blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/dialexity.com\/blog\/wp-json\/wp\/v2\/comments?post=1848"}],"version-history":[{"count":136,"href":"https:\/\/dialexity.com\/blog\/wp-json\/wp\/v2\/posts\/1848\/revisions"}],"predecessor-version":[{"id":2636,"href":"https:\/\/dialexity.com\/blog\/wp-json\/wp\/v2\/posts\/1848\/revisions\/2636"}],"wp:attachment":[{"href":"https:\/\/dialexity.com\/blog\/wp-json\/wp\/v2\/media?parent=1848"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/dialexity.com\/blog\/wp-json\/wp\/v2\/categories?post=1848"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/dialexity.com\/blog\/wp-json\/wp\/v2\/tags?post=1848"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}