By Inês Hipolito/Deborah Pirchner, science writer Frontiers
Inês Hipólito is a highly accomplished researcher, recognized for her work in leading journals and contributions as a co-editor. He has received research awards including the prestigious Talent Grant from the University of Amsterdam in 2021. After his PhD, he held positions at the Berlin School of Mind and Brain and the Humboldt-Universität zu Berlin. Currently, he is a tenured lecturer in AI philosophy at Macquarie University, with a focus on cognitive development and the interaction between augmented cognition (AI) and the sociocultural environment.
Inês is co-leading a consortium project in ‘Exploring and Designing Urban Density. Neurourbanism as a New Approach to Global Health,’ funded by the Berlin University Alliance. He also serves as an AI ethicist at Verses.
Outside of his research, he co-founded and served as vice president of the International Society for the Philosophy of the Sciences of the Mind. Inês is the host of the thought-provoking podcast ‘The PhilospHER’s Way’ and actively contributed to the Committee on Women in Philosophy and the Committee on Diversity and Inclusiveness at the Australasia Association of Philosophy from 2017 to 2020.
As part of us Frontier Scientist series, Hipólito meets 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 desire to understand our experience of the world has been a driving force in my life. Interacting with inspiring teachers and mentors throughout my education further fueled my motivation to explore the possibilities of objective understanding. This led me to pursue a multidisciplinary path in philosophy and neuroscience, embracing cognitive science’s original intent for interdisciplinary collaboration. I believe that by bridging the disciplinary gap, we can gain an understanding of the human mind and its interaction with the world. This integrative approach allows me to contribute scientific knowledge and real-world applications that benefit individuals and society as a whole.
Can you tell us about the research you are working on?
My research is centered on cognitive development and its implications for the cognitive science of AI. Sociocultural context plays an important role in shaping cognitive development, from the fundamental cognitive processes to the more sophisticated and semantically sophisticated cognitive activities that we acquire and engage in.
As our world becomes increasingly infused with AI, my research focuses on two main aspects. First, I investigate how intelligent environments such as online spaces, virtual reality, and digital citizenship influence context-dependent cognitive development. By exploring these impacts of the environment, I aim to gain insight into how cognition is shaped and adapted in this technologically mediated context.
Second, I examine how AI design emerges from specific sociocultural settings. Instead of simply reflecting society, AI design embodies people’s values and aspirations. I explore the complex relationship between AI and its sociocultural origins to understand how technology can shape and be affected by the context in which it is developed.
Why do you think your research is important?
The aim of my work is to contribute to the understanding of the complex relationship between cognition and AI, focusing on the sociocultural dynamics that influence cognitive development and the design of artificial intelligence systems. I am deeply interested in understanding and the paradoxical nature of AI development and its social impact: while technology has historically improved lives, AI has also brought attention to the problematic biases and segregation highlighted in the feminist technoscience literature.
As AI evolves, it’s critical to ensure that progress benefits everyone and doesn’t perpetuate historical inequalities. Inclusivity and equality must be prioritized, challenging the dominant narrative that favors certain groups, especially white men. Recognizing that AI technologies embody our implicit biases and reflect our attitudes toward diversity and our relationship with nature allows us to more effectively navigate the ethical and social implications of AI.
Are there common misconceptions about this area of research? How do you deal with it?
This common misconception of viewing the mind as a computer has significant implications for the design of AI and our understanding of cognition. While cognition is seen as a simple input-output process in the brain, it ignores the complexities of human experience and the biases embedded in AI design. This reductionist view fails to explain the importance of embodied interaction, cognitive development, mental health, well-being, and societal equity.
This subjective experience of the world cannot be reduced to mere information processing, as it is context dependent and filled with meanings that are partly constructed in societal power dynamics.
As the environment is increasingly permeated by AI, understanding how it is shaped by and shapes human experience requires investigation beyond understanding cognition as a (meaningless) information process. By recognizing the distributed and embodied nature of cognition, we can ensure that AI technologies are designed and integrated in ways that respect the complexity of the human experience, embrace ambiguity, and promote meaningful and just social interactions.
What areas of research would you like to see tackled in the coming years?
In the coming years, it is imperative to address several areas related to AI to shape a more inclusive and sustainable future:
Design AI to reduce bias and discrimination, ensuring equal opportunity for individuals of all backgrounds.
Make AI systems transparent and explainable, enabling people to understand how decisions are made and how to hold them accountable for unintended consequences.
Collaborate with various stakeholders to address biases, cultural sensitivities and challenges faced by marginalized communities in AI development.
Consider ecological impact, resource consumption, waste production and carbon footprint across the life cycle of AI technologies.
How can open science benefit your research reach and impact?
Publicly funded scientific knowledge must be freely available to conform with the principles of open science. Open science emphasizes transparency, collaboration and accessibility in scientific research and knowledge sharing. By openly sharing AI-related knowledge, including code, data, and algorithms, we encourage a wide variety of stakeholders to contribute their expertise, identify potential biases, and address ethical issues in tech.
Additionally, incorporating philosophical reasoning into the development of a philosophical theory of mind can inform ethical considerations and decision-making in the design and implementation of AI by researchers and policy makers. This transparent and collaborative approach enables critical assessment and improvement of AI technologies to ensure fairness, reduction of bias and overall equity.
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