The Human Side of Artificial Intelligence

Butkus, Matthew A.

doi:10.1007/s11948-020-00239-9

Cited by 5 publications

(3 citation statements)

References 31 publications

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“…Calls to avoid anthropomorphizing GPT are recurrent (Bender et al, 2021;Butkus, 2020;Coeckelbergh, 2021;Jebari & Lundborg, 2021;Kubes & Reinhardt, 2022;Shardlow & Przybyła, 2023). But anthropomorphizing is only referred to as projecting human qualities, particularly cognitive or emotional ones, to the machine.…”

Section: Anthropomorphising Gptmentioning

confidence: 99%

International Doctoral Students in the Area of “Sciences” at the University of the Basque Country (Upv/Ehu)

Barandika¹

2022

EDULEARN Proceedings

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is paper investigates the ontological characterization of Large Language Models (LLMs) like ChatGPT. Between in lationary and de lationary accounts, we pay special attention to their status as agents.is requires explaining in detail the architecture, processing, and training procedures that enable LLMs to display their capacities, and the extensions used to turn LLMs into agent-like systems. A ter a systematic analysis we conclude that a LLM fails to meet necessary and su ficient conditions for autonomous agency in the light of embodied theories of mind: the individuality condition (it is not the product of its own activity, it is not even directly a fected by it), the normativity condition (it does not generate its own norms or goals), and, partially the interactional asymmetry condition (it is not the origin and sustained source of its interaction with the environment). If not agents, then … what are LLMs? We argue that ChatGPT should be characterized as an interlocutor or linguistic automaton, a library-that-talks, devoid of (autonomous) agency, but capable to engage performatively on non-purposeful yet purpose-structured and purpose-bounded tasks. When interacting with humans, a "ghostly" component of the human-machine interaction makes it possible to enact genuine conversational experiences with LLMs. Despite their lack of sensorimotor and biological embodiment, LLMs textual embodiment (the training corpus) and resource-hungry computational embodiment, significantly transform existing forms of human agency. Beyond assisted and extended agency, the LLM-human coupling can produce midtended forms of agency, closer to the production of intentional agency than to the extended instrumentality of any previous technologies.

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Section: Anthropomorphising Gptmentioning

confidence: 99%

International Doctoral Students in the Area of “Sciences” at the University of the Basque Country (Upv/Ehu)

Barandika¹

2022

EDULEARN Proceedings

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“…The technological design and implementation of such concepts is anything but trivial and challenging on two counts. First, utilities to be optimized are difficult to grasp and determine or differ across stakeholders (Butkus, 2020 ). Second, the nascent stage of artificial moral agency still demands human agency.…”

Section: The Ethics Of Ai In Marketingmentioning

confidence: 99%

Leveraging Artificial Intelligence in Marketing for Social Good—An Ethical Perspective

Hermann

2021

J Bus Ethics

125

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Artificial intelligence (AI) is (re)shaping strategy, activities, interactions, and relationships in business and specifically in marketing. The drawback of the substantial opportunities AI systems and applications (will) provide in marketing are ethical controversies. Building on the literature on AI ethics, the authors systematically scrutinize the ethical challenges of deploying AI in marketing from a multi-stakeholder perspective. By revealing interdependencies and tensions between ethical principles, the authors shed light on the applicability of a purely principled, deontological approach to AI ethics in marketing. To reconcile some of these tensions and account for the AI-for-social-good perspective, the authors make suggestions of how AI in marketing can be leveraged to promote societal and environmental well-being.

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“…Autonomy in relation to AI applications and systems requires human agency (i.e., autonomous human decisions) and human oversight (Morley et al, 2020 ). As human researchers encounter difficulties to unambiguously grasp and determine utilities of R&D outcomes for different stakeholders, so does AI to an even higher degree (Butkus, 2020 ). Ethically controversial questions about environmental compatibility or toxicity of substances related to both humans and the environment necessitate human oversight and foresight (e.g., Floridi & Strait, 2020 ).…”

Section: Autonomymentioning

confidence: 99%

Ethical Artificial Intelligence in Chemical Research and Development: A Dual Advantage for Sustainability

Hermann

Hermann²,

Tremblay

2021

Sci Eng Ethics

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Artificial intelligence can be a game changer to address the global challenge of humanity-threatening climate change by fostering sustainable development. Since chemical research and development lay the foundation for innovative products and solutions, this study presents a novel chemical research and development process backed with artificial intelligence and guiding ethical principles to account for both process- and outcome-related sustainability. Particularly in ethically salient contexts, ethical principles have to accompany research and development powered by artificial intelligence to promote social and environmental good and sustainability (beneficence) while preventing any harm (non-maleficence) for all stakeholders (i.e., companies, individuals, society at large) affected.

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The Human Side of Artificial Intelligence

Cited by 5 publications

References 31 publications

International Doctoral Students in the Area of “Sciences” at the University of the Basque Country (Upv/Ehu)

International Doctoral Students in the Area of “Sciences” at the University of the Basque Country (Upv/Ehu)

Leveraging Artificial Intelligence in Marketing for Social Good—An Ethical Perspective

Ethical Artificial Intelligence in Chemical Research and Development: A Dual Advantage for Sustainability

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