Gaining new insights into the complex relationship between cognition and AI

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Gaining new insights into the complex relationship between cognition and AI

Inês Hipólito is an extremely accomplished researcher, recognized for her work in respected journals and her contributions as a co-editor. She has received research awards, including the prestigious Talent Fellowship from the University of Amsterdam in 2021. After her PhD, she held positions at the Berlin School of Mind and Brain and the Humboldt-Universität zu Berlin. She is currently a tenured lecturer in Philosophy of AI at Macquarie University, focusing on cognitive development and the interaction between augmented cognition (AI) and the sociocultural environment.

Inês is co-leading a consortium project “Urban Density Research and Design”. Neurourbanism as a new approach in global health’, funded by the Berlin University Alliance. She also serves as the AI ​​Ethicist at Verses.

In addition to her research, she co-founded and serves as vice president of the International Society for the Philosophy of Mind. Inês hosts the thought-provoking podcast ‘The PhilospHER’s Way’ and is an active contributor to the Australasian Philosophical Association’s Committee on Women in Philosophy and the Diversity and Inclusion Committee from 2017 to 2020.

As part of our Frontier Scientists series, Hipólito caught up with Frontiers to tell us about his career and research.

What inspired you to become a researcher?

Throughout my personal journey, my innate curiosity and passion for understanding our experience of the world have been driving forces in my life. Interacting with inspiring teachers and mentors during my studies further fueled my motivation to explore the possibilities of objective understanding. This led me to follow a multidisciplinary path in philosophy and neuroscience, embracing the original intent of cognitive science for interdisciplinary collaboration. I believe that by bridging disciplinary gaps we can gain an understanding of the human mind and its interaction with the world. This integrative approach enables me to contribute to both scientific knowledge and real-world applications that benefit individuals and society as a whole.

Can you tell us about the research you are currently working on?

My research is centered around cognitive development and its implications in the cognitive science of AI. Sociocultural contexts play a major role in shaping cognitive development, ranging from fundamental cognitive processes to more advanced, semantically complex cognitive activities that we acquire and engage in.

As our world becomes increasingly penetrated by AI, my research focuses on two main aspects. First, I explore how smart environments such as online spaces, virtual reality, and digital citizenship influence context-dependent cognitive development. By exploring the impact of these environments, I aim to gain insight into how cognition is shaped and adapted within these technologically mediated contexts.

Second, I consider how AI design emerges from specific sociocultural conditions. Rather than simply reflecting society, AI design embodies societal values ​​and aspirations. I explore the complex relationship between AI and its sociocultural origins to understand how technology can both shape and be influenced by the context in which it is developed.

Why do you think your research is important?

The goal of my work is to contribute to the understanding of the complex relationship between cognition and AI by focusing on the sociocultural dynamics that influence both cognitive development and the design of artificial intelligence systems. I am particularly interested in understanding the paradoxical nature of the development of AI and its impact on society: while technology has historically improved life, AI has also drawn attention to the problematic biases and segregation highlighted in feminist technoscience literature.

As AI advances, it is critical to ensure that progress benefits everyone and does not perpetuate historical inequalities. Inclusion and equality must be prioritized, countering dominant narratives that favor certain groups, especially white men. Recognizing that AI technologies embody our implicit biases and reflect our attitudes toward diversity and our relationship to the natural world allows us to more effectively navigate the ethical and societal implications of AI.

Are there any common misconceptions about this area of ​​study? How would you approach them?

The common misconception of viewing the mind as a computer has significant implications for AI design and our understanding of cognition. When cognition is viewed as a simple input-output process in the brain, it ignores the embodied complexity of human experience and the biases built into AI design. This reductionist view fails to account for the importance of embodied interaction, cognitive development, mental health, well-being, and social justice.

This subjective experience of the world cannot be reduced to simple information processing, as it is context-dependent and imbued with meanings partially constructed in social power dynamics.

As the environment is increasingly permeated by AI, understanding how it is shaped by and shapes human experience requires research beyond understanding cognition as (meaningless) information processes. By acknowledging the distributed and embodied nature of cognition, we can ensure that AI technologies are designed and integrated in a way that respects the complexity of human experience, embraces ambiguity, and promotes meaningful and equitable societal interactions.

What are some areas of research you would like to explore in the coming years?

In the coming years, it is critical to tackle several AI-related areas to shape a more inclusive and sustainable future:

Design AI to reduce bias and discrimination by ensuring equal opportunities for people from different backgrounds.

Make AI systems transparent and explainable, allowing humans to understand how decisions are made and how to hold them accountable for unintended consequences.

Collaborating with diverse stakeholders to address biases, cultural sensitivities, and challenges facing marginalized communities in AI development.

Consider the environmental impact, resource consumption, waste generation and carbon footprint throughout the lifecycle of AI technologies.

How has open science helped the scope and impact of your research?

Scientific knowledge that is publicly funded must be freely available to align with the principles of open science. Open science emphasizes transparency, collaboration, and accessibility in research and knowledge dissemination. By openly sharing AI-related knowledge, including code, data, and algorithms, we encourage diverse stakeholders to contribute their expertise, identify potential biases, and address ethical issues within the technological sciences.

Furthermore, incorporating philosophical considerations into the development of a theory of philosophy of mind can contribute to ethical deliberations and decision-making in the design and implementation of AI by researchers and policy makers. This transparent and collaborative approach enables critical evaluation and improvement of AI technologies to ensure fairness, reduction of bias and overall fairness.

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Journal reference:

Ippolit, I. et al. (2023) Active artificial intelligence: subverting gender norms in human-robot interaction. Frontiers in Neurorobotics. doi.org/10.3389/fnbot.2023.1149303.

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