TY  - JOUR
AU  - Bojic, Ljubisa
PY  - 2024
UR  - http://rifdt.instifdt.bg.ac.rs/123456789/3816
AB  - The recent growing concerns surrounding the pervasive adoption of generative AI can be traced back to the long-standing influence of AI algorithms that have predominantly served as content curators on large online platforms. These algorithms are used by online services and platforms to decide what content to show and in what order, and they can have a negative impact, including the spread of misinformation, social polarization, and echo chambers around important topics. Frances Haugen, a former Facebook employee turned whistleblower, has drawn significant public attention to this issue by revealing the company's alleged knowledge about the negative impacts of their own algorithms. Additionally, a recent initiative to ban TikTok as a threat to US national security indicates the influence of recommender systems. The objective of this study is threefold. The first goal is to provide an exhaustive evaluation of the profound worldwide influence exerted by algorithm-based recommendations. The second goal is to determine the degree of priority accorded by the scientific community to pivotal subjects in recommender systems discussions, such as misinformation, polarization, addiction, emotional contagion, privacy, and bias. Finally, the third goal is to assess whether the level of scientific research and discourse is commensurate with the significant impact these recommendation systems have globally. The research concludes the impact of recommender systems on society has been largely neglected by the scientific community, despite the fact that more than half of the world's population interacts with them on a daily basis. This becomes especially apparent when considering that algorithms exert influence not just on major societal issues but on every aspect of a user's online experience. The potential consequences for humanity are discussed, such as addiction to technology, weakening relations between humans, and the homogenizing effects on human minds. One possible direction to address the challenges posed by these algorithms is the application of algorithmic regulation to promote content diversity and facilitate democratic engagement, such as the tripartite solution which is elaborated upon in the conclusion. Therefore, future research should not only be centered around further evaluating influence of this technology, but also the analysis of how such systems can be regulated. A broader conversation among all stakeholders should be evoked on these potential approaches, aiming to align AI with societal values and enhance human well-being.
PB  - Elsevier
T2  - Futures
T1  - AI alignment: Assessing the global impact of recommender systems
IS  - 103383
DO  - 10.1016/j.futures.2024.103383
ER  - 

@article{
author = "Bojic, Ljubisa",
year = "2024",
abstract = "The recent growing concerns surrounding the pervasive adoption of generative AI can be traced back to the long-standing influence of AI algorithms that have predominantly served as content curators on large online platforms. These algorithms are used by online services and platforms to decide what content to show and in what order, and they can have a negative impact, including the spread of misinformation, social polarization, and echo chambers around important topics. Frances Haugen, a former Facebook employee turned whistleblower, has drawn significant public attention to this issue by revealing the company's alleged knowledge about the negative impacts of their own algorithms. Additionally, a recent initiative to ban TikTok as a threat to US national security indicates the influence of recommender systems. The objective of this study is threefold. The first goal is to provide an exhaustive evaluation of the profound worldwide influence exerted by algorithm-based recommendations. The second goal is to determine the degree of priority accorded by the scientific community to pivotal subjects in recommender systems discussions, such as misinformation, polarization, addiction, emotional contagion, privacy, and bias. Finally, the third goal is to assess whether the level of scientific research and discourse is commensurate with the significant impact these recommendation systems have globally. The research concludes the impact of recommender systems on society has been largely neglected by the scientific community, despite the fact that more than half of the world's population interacts with them on a daily basis. This becomes especially apparent when considering that algorithms exert influence not just on major societal issues but on every aspect of a user's online experience. The potential consequences for humanity are discussed, such as addiction to technology, weakening relations between humans, and the homogenizing effects on human minds. One possible direction to address the challenges posed by these algorithms is the application of algorithmic regulation to promote content diversity and facilitate democratic engagement, such as the tripartite solution which is elaborated upon in the conclusion. Therefore, future research should not only be centered around further evaluating influence of this technology, but also the analysis of how such systems can be regulated. A broader conversation among all stakeholders should be evoked on these potential approaches, aiming to align AI with societal values and enhance human well-being.",
publisher = "Elsevier",
journal = "Futures",
title = "AI alignment: Assessing the global impact of recommender systems",
number = "103383",
doi = "10.1016/j.futures.2024.103383"
}

Bojic, L.. (2024). AI alignment: Assessing the global impact of recommender systems. in Futures
Elsevier.(103383).
https://doi.org/10.1016/j.futures.2024.103383

Bojic L. AI alignment: Assessing the global impact of recommender systems. in Futures. 2024;(103383).
doi:10.1016/j.futures.2024.103383 .

Bojic, Ljubisa, "AI alignment: Assessing the global impact of recommender systems" in Futures, no. 103383 (2024),
https://doi.org/10.1016/j.futures.2024.103383 . .

TY  - JOUR
AU  - Tucaković, Lana
AU  - Bojic, Ljubisa
AU  - Nikolić, Nemanja
PY  - 2022
UR  - http://rifdt.instifdt.bg.ac.rs/123456789/2627
AB  - In recent years, online dating websites, applications, and social media have become increasingly popular tools for finding romantic and/or sexual partners. Individual differences in personality traits predict the use of online dating websites and applications and also influence the motives for their use. Previous work regarding mating strategies in the context of online dating has focused on the Dark Tetrad concept of malevolent personality while ignoring the Light Triad concept of beneficent personality. Light and dark personality traits are not seen as polar opposites as they supplement each other. Thus, the current study aimed to explore the utility of both light (i.e., Faith in Humanity, Humanism, and Kantianism) and dark (i.e., Machiavellianism, narcissism, psychopathy, and sadism) personality traits in predicting mating strategies in the online context. A total of 216 participants, ages 20 to 56, which used online dating sites, apps, and social media for finding partners in the past year, completed an online questionnaire assessing Dark Tetrad traits, Light Triad traits, and mating orientations. Narcissism, psychopathy, and sadism positively correlated, while Faith in Humanity and Kantianism negatively correlated with short-term mating. However, only Faith in Humanity was a significant predictor of short-term mating. As for long-term mating, the results have shown that it is negatively related to psychopathy and sadism, while it is positively related to all Light Triad traits. Faith in Humanity, Humanism, and Kantianism were significant predictors of long-term mating. These findings highlight the utility of the Dark Tetrad and Light Triad traits in mating orientation research.
PB  - PsychOpen
T2  - Interpersona: An International Journal on Personal Relationships
T1  - The Battle between Light and Dark Side of Personality: How Light and Dark Personality Traits Predict Mating Strategies in the Online Context
DO  - 10.23668/psycharchives.5621
ER  - 

@article{
author = "Tucaković, Lana and Bojic, Ljubisa and Nikolić, Nemanja",
year = "2022",
abstract = "In recent years, online dating websites, applications, and social media have become increasingly popular tools for finding romantic and/or sexual partners. Individual differences in personality traits predict the use of online dating websites and applications and also influence the motives for their use. Previous work regarding mating strategies in the context of online dating has focused on the Dark Tetrad concept of malevolent personality while ignoring the Light Triad concept of beneficent personality. Light and dark personality traits are not seen as polar opposites as they supplement each other. Thus, the current study aimed to explore the utility of both light (i.e., Faith in Humanity, Humanism, and Kantianism) and dark (i.e., Machiavellianism, narcissism, psychopathy, and sadism) personality traits in predicting mating strategies in the online context. A total of 216 participants, ages 20 to 56, which used online dating sites, apps, and social media for finding partners in the past year, completed an online questionnaire assessing Dark Tetrad traits, Light Triad traits, and mating orientations. Narcissism, psychopathy, and sadism positively correlated, while Faith in Humanity and Kantianism negatively correlated with short-term mating. However, only Faith in Humanity was a significant predictor of short-term mating. As for long-term mating, the results have shown that it is negatively related to psychopathy and sadism, while it is positively related to all Light Triad traits. Faith in Humanity, Humanism, and Kantianism were significant predictors of long-term mating. These findings highlight the utility of the Dark Tetrad and Light Triad traits in mating orientation research.",
publisher = "PsychOpen",
journal = "Interpersona: An International Journal on Personal Relationships",
title = "The Battle between Light and Dark Side of Personality: How Light and Dark Personality Traits Predict Mating Strategies in the Online Context",
doi = "10.23668/psycharchives.5621"
}

Tucaković, L., Bojic, L.,& Nikolić, N.. (2022). The Battle between Light and Dark Side of Personality: How Light and Dark Personality Traits Predict Mating Strategies in the Online Context. in Interpersona: An International Journal on Personal Relationships
PsychOpen..
https://doi.org/10.23668/psycharchives.5621

Tucaković L, Bojic L, Nikolić N. The Battle between Light and Dark Side of Personality: How Light and Dark Personality Traits Predict Mating Strategies in the Online Context. in Interpersona: An International Journal on Personal Relationships. 2022;.
doi:10.23668/psycharchives.5621 .

Tucaković, Lana, Bojic, Ljubisa, Nikolić, Nemanja, "The Battle between Light and Dark Side of Personality: How Light and Dark Personality Traits Predict Mating Strategies in the Online Context" in Interpersona: An International Journal on Personal Relationships (2022),
https://doi.org/10.23668/psycharchives.5621 . .