4^th World Congress on
Psychiatry & Mental Health Nursing

Biography:

As CEO of The Adaption Apex Lab and director of OCEANH2.0, Aram Cargill is also on the board of directors for Ledsen as well as a non-executive director a Kanga innovations. Having pioneered the adaption of DARE (Deception Analysis Reasoning Engine) for advanced lexical psychometric testing through mobile phone technology. Acting as a keynote speaker and chair for the Annual Congress of Psychiatry in Paris in 2018. 2019 is set to be a big year with the launch of OceanH2.0 machine learning operational psychology within an artificial intelligence framework to further advance psychographic information for greater personalisation of the relationship between man and machine.

Abstract:

Personality type refers to the psychological classification of different types of individuals. Personality types are sometimes distinguished from personality traits, with the latter embodying a smaller grouping of behavioural tendencies

in 2011, Kibeom Lee and Michael Ashton. Ashton made significate research grounds for the inclusion of a sixth factor, referred to as the H factor (Humility and Honesty trait) (Ashton, Michael C.; Lee, Kibeom 2011) into Personality taxonomy, widely known as the big 5 (or OCEAN: openness, conscientiousness, extraversion, agreeableness, and neuroticism)

 

Personality taxonomy has predominately been measured through language-based questionnaires (Lexical theory) which proves problematic and unreliable, especially when measuring traits such a humility and honesty. In testing for the H factor personality trait, it was difficult to not have negative language association and around the question of humility and honesty, which compromised the data. This lead us in developing more accurate indicators. 

 

By adapting DARE (deception analysis reasoning engine) we can bring a more observational approach and detect greater indication of deceptive response which in its self-results in more accurate metrics of honesty and humility.

(OCEANH2.0) 

Description:

In adding the H factor (Humility and Honesty) to the Big 5 psychometric trait scale evaluation, we have introduced a two-tiered system evaluation and scaling framework.

Because humility and honesty are hard to gain authentic evaluation responses for. The main response for this is that even an honest person is not inclined to recognize various cognitive bias to little white lies they might tell. (even to themselves to potentially keep the peace) The cultural stigma of admitting to being untruthful or not humble or authentic in their need for recognition.

There is the limitation of lexical theory (language based) to have to potentially perceived negative framing or cognition to the type of question needed to scale humility and honesty, especially regarding cultural and societal framing of this particular trait metric.

To assist in a more accurate reading of the H factor within an individual, we have adopted a more observational phycological approach through artificial intelligence. By using an adaptation of DARE (deception analysis reasoning engine), we were able to gain a more accurate and therefore a more trust worthy evolution scale of the honesty and humility of the person or user.

This was achieved in greater evaluation of the potentially deceptive nature of the response or inauthentic indicators of humility and honesty.       

First the user is asked to either confirm or deny a statement. This allows the detection of potentially deceptive responses. The user is asked to repeat, to either concur or negate the statement.

Ocean H2.0 allows a departure lexical theory questionnaire into more observational psychological realms through machine learning principle applied through artificial intelligence. This allows for far more accurate psychometrics, but more importantly more accurate profiling of human psychology; so that machines can better understand human beings as individuals. What does this mean?  Better machine learning to assist as mentors and accountability buddies to assist in breaking addiction, learning, performance enhancement and ultimately bridging the gap between what we say and what we do by learning what makes us, us.