AI in Finance: Challenges, Techniques and Opportunities

Cao, Longbing

doi:10.48550/arxiv.2107.09051

Cited by 4 publications

(6 citation statements)

References 157 publications

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“…However, subsequent testing indicated that the chatbot still provided suggestions for suicide, raising questions about the effectiveness of these safety measures [91]. This aligns with the challenges discussed by [73], who emphasizes the need for robust testing methodologies to improve the predictability of AI systems in real-world conditions. The incident has also prompted discussions about the need for the greater regulation and oversight of AI technologies.…”

Section: Ai Chatbots and Mental Health: Navigating Ethical And Safety...mentioning

confidence: 85%

“…The Tay chatbot debacle provided a profound learning experience for the AI industry, underscoring the critical need for an ethical AI design that aligns with societal values and norms. Robust testing is essential before AI systems are released to uncover and mitigate potential vulnerabilities that malicious actors could exploit [73]. The incident also demonstrated the necessity for continuous monitoring and moderation to swiftly address harmful content disseminated when AI interacts with the public.…”

Section: Tay's Troubles: a Pivotal Moment In Ai Development And The Q...mentioning

confidence: 99%

“…The robust validation and testing of AI systems in real-world scenarios are crucial for identifying and mitigating unpredictability [81]. Rigorous evaluation processes are essential for testing the reliability and predictability of AI systems before deployment, particularly in finance, where AI decisions can have significant economic implications [73]. Moreover, establishing comprehensive regulatory frameworks for AI use can help manage the risks associated with unpredictability by setting standards for AI safety, accountability, and transparency [80].…”

Section: And Then There Was Sydney: the Conundrum Of Ai Autonomy And ...mentioning

confidence: 99%

“…The black-box nature of AI algorithms in healthcare can hinder physicians' ability to explain decisions to patients, leading to accountability issues for adverse outcomes. Similarly, in the finance sector, AI unpredictability manifests in the form of security, model, and market risks, necessitating careful mitigation strategies to ensure the responsible use of AI in financial systems [73]. To address these challenges, developing and adopting technologies such as Explainable AI (XAI) play a pivotal role in clarifying the inner workings of AI systems, thereby building a foundation of trust with users [75].…”

Section: Charting the Future Of Ai: Ethical Integration And Cognitive...mentioning

confidence: 99%

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The Era of Artificial Intelligence Deception: Unraveling the Complexities of False Realities and Emerging Threats of Misinformation

Williamson,

Prybutok

2024

Information

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This study delves into the dual nature of artificial intelligence (AI), illuminating its transformative potential that has the power to revolutionize various aspects of our lives. We delve into critical issues such as AI hallucinations, misinformation, and unpredictable behavior, particularly in large language models (LLMs) and AI-powered chatbots. These technologies, while capable of manipulating human decisions and exploiting cognitive vulnerabilities, also hold the key to unlocking unprecedented opportunities for innovation and progress. Our research underscores the need for robust, ethical AI development and deployment frameworks, advocating a balance between technological advancement and societal values. We emphasize the importance of collaboration among researchers, developers, policymakers, and end users to steer AI development toward maximizing benefits while minimizing potential harms. This study highlights the critical role of responsible AI practices, including regular training, engagement, and the sharing of experiences among AI users, to mitigate risks and develop the best practices. We call for updated legal and regulatory frameworks to keep pace with AI advancements and ensure their alignment with ethical principles and societal values. By fostering open dialog, sharing knowledge, and prioritizing ethical considerations, we can harness AI’s transformative potential to drive human advancement while managing its inherent risks and challenges.

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Section: Ai Chatbots and Mental Health: Navigating Ethical And Safety...mentioning

confidence: 85%

Section: Tay's Troubles: a Pivotal Moment In Ai Development And The Q...mentioning

confidence: 99%

Section: And Then There Was Sydney: the Conundrum Of Ai Autonomy And ...mentioning

confidence: 99%

Section: Charting the Future Of Ai: Ethical Integration And Cognitive...mentioning

confidence: 99%

See 2 more Smart Citations

The Era of Artificial Intelligence Deception: Unraveling the Complexities of False Realities and Emerging Threats of Misinformation

Williamson,

Prybutok

2024

Information

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“…One more difference between this study and the earlier one concerns the sophistication of the machines. Following the direction of technological innovations in finance (Cao, 2021;Goodell et al, 2021), participants in both our study and the benchmarked study rated decisions that were suggested by machine learning algorithms. However, they represented different levels of sophistication.…”

Section: The Sophistication Of Machinesmentioning

confidence: 99%

Will the use of machines to identify negative activist investments backfire? Experimental evidence

Niszczota¹,

Kaszás²

2022

Preprint

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Current research does not resolve how people will judge harmful activist investments if machines (machine learning algorithms) are involved in the investment process as advisors, and not the ones “pulling the trigger”. On the one hand, machines might diffuse responsibility for making a socially responsible, but harmful investment. On the other hand, machines could exacerbate the blame that is assigned to the investment fund, which can be penalized for outsourcing part of the decision process to an algorithm. We attempted to resolve this issue experimentally. In our experiment (N = 956), participants judge either a human research team or a machine learning algorithm as the source of advice to the investment team to short-sell a company that they suspect of committing financial fraud. Results suggest that investment funds will be similarly blameworthy for an error regardless of using human or machine intelligence to support their decision to short-sell a company. This finding highlights a novel and relevant circumstance in which reliance on algorithms does not backfire by making the final decision-maker (e.g., an investment fund) more blameworthy. Nor does it lessen the perceived blameworthiness of the final decision-maker, by making algorithms into “electronic scapegoats” for providing well-intended but harmful advice.

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Exploring the role of artificial intelligence technology in empowering women-led startups

Alateeg,

Al-Ayed

2024

Knowledge and Performance Management

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The study aims to investigate how artificial intelligence (AI) influences women-led startups in Saudi Arabia, aiming to understand their unique experiences, challenges, and opportunities within the AI technology landscape. This study used a qualitative method, conducting 16 in-depth interviews with women entrepreneurs operating businesses in Saudi Arabia. The analysis was performed using thematic analysis with NVivo 12, uncovering key themes and insights. The findings reveal that cultural norms, societal expectations, limited awareness, and financial constraints are directly associated with women’s involvement in AI-driven businesses. Cultural biases emerged as impediments, underscoring the need for targeted interventions such as awareness campaigns and educational initiatives to dismantle ingrained biases and foster an environment that recognizes and celebrates the contributions of women in the tech and AI sectors. Educational programs, collaborations between academia and industry, and mentorship initiatives were identified as pivotal components to prepare women entrepreneurs to navigate the intricate landscape of AI adoption. Financial inclusion emerged as a critical pillar, advocating for equitable access to funding and resources tailored specifically for women-led AI startups. The study further emphasizes the importance of fostering supportive ecosystems that extend beyond financial aid. Creating networks for mentorship, guidance, and collaboration provides women entrepreneurs with platforms to share experiences and resources, enhancing resilience and the potential for success in the AI landscape. Acknowledgment The authors extend their appreciation to the Arab Open University for funding this work through research fund No. AOUKSA-524008.

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AI in Finance: Challenges, Techniques and Opportunities

Cited by 4 publications

References 157 publications

The Era of Artificial Intelligence Deception: Unraveling the Complexities of False Realities and Emerging Threats of Misinformation

The Era of Artificial Intelligence Deception: Unraveling the Complexities of False Realities and Emerging Threats of Misinformation

Will the use of machines to identify negative activist investments backfire? Experimental evidence

Exploring the role of artificial intelligence technology in empowering women-led startups

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