Introducing Robotic Scientists: Explorations into New Dimensions of Scientific Objectivity and Creativity
Öz
This study investigates the epistemological and sociological implications of robotic scientists—autonomous systems capable of hypothesis generation, experimentation, and inferences are examined in terms of objectivity in the context of contemporary science. However, scholars such as S. Harding, and H. Douglas have shown that science is inherently value laden. Robotic scientists complicate this discourse: while designed to minimize human biases, they reintroduce values via algorithmic design and data selection. Through cases like the Robot Scientist “Adam” and the autonomous robotic chemist developed at the University of Liverpool; the article illustrates how these systems can independently conduct large-scale experiments with remarkable consistency. Their ability to generate and test hypotheses reconfigures how scientific agency and authorship are understood, demanding a redefinition of objectivity as both an epistemic and procedural standard. The article also addresses the question of robotic creativity, using Boden’s framework to suggest that such systems already demonstrate exploratory creativity. Supported by international initiatives like the OECD’s “Nobel-Turing Challenge” the potential for robots to play more innovative scientific roles is becoming more tangible. Sociologically, robotic scientists challenge established institutional norms. Drawing on Latour’s Actor-Network Theory and Lamola’s concept of the “robosphere,” the article argues that these machines are not just tools but participants in socio-technical networks. They provoke reevaluation of concepts like expertise, community, and legitimacy. Robotic scientists do not merely enhance traditional research—they reshape the norms, values, and boundaries of science itself. Their emergence calls for interdisciplinary inquiry to address the ethical, philosophical, and institutional frameworks that must guide this transformation.
Anahtar Kelimeler
Robotic Scientists Scientific Objectivity Human–Machine Interaction
Kaynakça
- Besold, T. R., Garcez, A. d’Avila, Bader, S., Bowman, H., Domingos, P., Hitzler, P., … Zaverucha, G. (2017). Neural-Symbolic Learning and Reasoning: A Survey and Interpretation (Version 1). Version 1. arXiv. https://doi.org/10.48550/ARXIV.1711.03902.
- Boden, M. A. (2004). The creative mind: Myths and mechanisms (2nd ed.). Routledge. (pp. 3–8). Burrell, J. (2016). “How the machine ‘thinks’: Understanding opacity in machine learning algorithms”. Big Data & Society, 3(1), 2053951715622512. https://doi. org/10.1177/2053951715622512.
- Collins, H. (2010). Tacit and explicit knowledge. University of Chicago Press. (pp. 125–132). Daston, L., & Galison, P. (2010). Objectivity (First paperback edition). New York, NY: Zone Books.
- Douglas, H. (2009). Science, policy, and the value-free ideal. University of Pittsburgh Press. (pp. 86–89).
- Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., … Vayena, E. (2018). “AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations”. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5.
- Fricker, M. (2007). Epistemic Injustice: Power and the Ethics of Knowing (1st ed.). Oxford University PressOxford. https://doi.org/10.1093/acprof:oso/9780198237907.001.0001.
- Fuller, S. (2006). The philosophy of science and technology studies (Online-Ausg). New York: Routledge.
- Fuller, S. (2007). New frontiers in science and technology. Cambridge: Polity.
- Harding, S. (1991). “What Is Feminist Epistemology?”. In Thinking from Women’s Lives.
- Whose Science? Whose knowledge? (pp. 105–137). Cornell University Press. JSTOR. Retrieved from http://www.jstor.org/stable/10.7591/j.ctt1hhfnmg.8
- Harding, S. (1991). Whose science? Whose knowledge? Thinking from women’s lives. Cornell University Press. (pp. 112–115).
- Hempel, Carl G., & Oppenheim, P. (1948). “Studies in the Logic of Explanation”. Philosophy of Science, 2(15), 135–175. Retrieved from https://www.jstor.org/stable/185169
- Hempel, Carl Gustav. (2001). The Philosophy of Carl G. Hempel: Studies in science, explanation, and rationality ( J. H. Fetzer, Ed.). Oxford New York: Oxford University Press.
- King, R. D., Rowland, J., Oliver, S. G., Young, M., Aubrey, W., Byrne, E., … Clare, A. (2009). “The Automation of Science”. Science, 324(5923), 85–89. https://doi.org/10.1126/ science.1165620
- Knorr Cetina, K. (1999). Epistemic cultures: How the sciences make knowledge. Harvard University Press. (pp. 183–185).
- Lamola, M. J. (2022). “On the robosphere: A philosophical explication of the sociotechnical status of social robots”. International Journal of Social Robotics, 14, 1199– 1209. https://doi.org/10.1007/s12369-021-00840-3.
- Latour, B. (1987). Science in action: How to follow scientists and engineers through society. Harvard University Press. (pp. 70–72).
- Lipton, Z. C. (2018). “The Mythos of Model Interpretability: In machine learning, the concept of interpretability is both important and slippery”. Queue, 16(3), 31–57. https://doi.org/10.1145/3236386.3241340
- Longino, H. E. (2020). Science as Social Knowledge: Values and Objectivity in Scientific Inquiry. Princeton University Press. https://doi.org/10.2307/j.ctvx5wbfz
- OECD. (2023). Artificial intelligence in science: Challenges, opportunities and the future of research. OECD Publishing. https://doi.org/10.1787/a8d820bd-en (pp. 10–15).
- Putnam, H. (1964). “Robots: Machines or artificially created life?”. The Journal of Philosophy, 61(21), 668–691. https://doi.org/10.2307/2023045 (pp. 668–670).
- Winner, L. (1980). “Do Artifacts Have Politics?”. Daedalus, 109(1), 121–136. JSTOR. Retrieved from http://www.jstor.org/stable/20024652
- World Economic Forum. (2020). This robot scientist conducted experiments by itself during COVID-19 lockdown. https://www.weforum.org/agenda/2020/08/robot-scientistautonomous-chemistry-university-of-liverpool.
Öz
Bu çalışmada hipotez üretme, deney yürütme ve bilimsel çıkarım yapma kapasitesine sahip otonom sistemler olan robotik bilimcilerin, çağdaş bilim bağlamında epistemolojik ve sosyolojik etkileri nesnellik açından incelenmektedir. Ancak S. Harding ve H. Douglas gibi araştırmacılar, bilimin doğası gereği değer yüklü olduğunu ortaya koymuştur. Robotik bilimciler bu tartışmayı karmaşıklaştırmaktadır: İnsan önyargılarını azaltmak üzere tasarlansalar da, algoritmik tasarım ve veri seçimi yoluyla yeni değer katmanlarını sisteme dahil ederler. “Adam” adlı Robot Bilimci ve Liverpool Üniversitesi’nde geliştirilen kimyager otonom robot ve benzeri örnekler, bu sistemlerin büyük ölçekli deneyleri bağımsız ve tutarlı biçimde gerçekleştirebildiğini göstermektedir. Hipotez üretme ve test etme becerileri, bilimsel öznellik ve yazarlık gibi kavramların yeniden tanımlanmasını gerektirebilir.. Bu durum, nesnelliğin yalnızca epistemik değil aynı zamanda işlemsel bir standart olarak yeniden düşünülmesine yol açabilir. Ayrıca, Boden’in çerçevesi doğrultusunda robotik yaratıcılık meselesini ve bu sistemlerin halihazırda keşfedici düzeyde yaratıcı işlevler gösterdiği görüşüne makalede yer verilmiştir. OECD’nin “Nobel-Turing Meydan Okuması” gibi uluslararası girişimleri de robotların bilimsel yenilik süreçlerine aktif biçimde katılabileceklerini göstermektedir. Sosyolojik olarak, robotik bilimciler bilimsel kurumların yerleşik normlarını zorlamayabilir. Latour’un Aktör-Ağ Kuramı ve Lamola’nın “robosfer” kavramı aracılığıyla, bu makinelerin yalnızca araç değil, sosyo-teknik ağlarda etkin aktörler olduğu öne sürülmektedir. Robotik bilimciler yalnızca bilimsel araştırmayı geliştirmekle kalmaz, bilimin normlarını, değerlerini ve sınırlarını da yeniden şekillendirebilir. Bu dönüşümün etik, felsefi ve kurumsal temellerle uyumlu biçimde ilerleyebilmesi için disiplinler arası bir çabaya ihtiyaç duyulmaktadır. Bu makalede bu çabanın genel çerçevesi çizilmeye çalışılacaktır.
Anahtar Kelimeler
Robotik Bilimciler Bilimsel Nesnellik İnsan–Makine Etkileşimi
Kaynakça
- Besold, T. R., Garcez, A. d’Avila, Bader, S., Bowman, H., Domingos, P., Hitzler, P., … Zaverucha, G. (2017). Neural-Symbolic Learning and Reasoning: A Survey and Interpretation (Version 1). Version 1. arXiv. https://doi.org/10.48550/ARXIV.1711.03902.
- Boden, M. A. (2004). The creative mind: Myths and mechanisms (2nd ed.). Routledge. (pp. 3–8). Burrell, J. (2016). “How the machine ‘thinks’: Understanding opacity in machine learning algorithms”. Big Data & Society, 3(1), 2053951715622512. https://doi. org/10.1177/2053951715622512.
- Collins, H. (2010). Tacit and explicit knowledge. University of Chicago Press. (pp. 125–132). Daston, L., & Galison, P. (2010). Objectivity (First paperback edition). New York, NY: Zone Books.
- Douglas, H. (2009). Science, policy, and the value-free ideal. University of Pittsburgh Press. (pp. 86–89).
- Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., … Vayena, E. (2018). “AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations”. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5.
- Fricker, M. (2007). Epistemic Injustice: Power and the Ethics of Knowing (1st ed.). Oxford University PressOxford. https://doi.org/10.1093/acprof:oso/9780198237907.001.0001.
- Fuller, S. (2006). The philosophy of science and technology studies (Online-Ausg). New York: Routledge.
- Fuller, S. (2007). New frontiers in science and technology. Cambridge: Polity.
- Harding, S. (1991). “What Is Feminist Epistemology?”. In Thinking from Women’s Lives.
- Whose Science? Whose knowledge? (pp. 105–137). Cornell University Press. JSTOR. Retrieved from http://www.jstor.org/stable/10.7591/j.ctt1hhfnmg.8
- Harding, S. (1991). Whose science? Whose knowledge? Thinking from women’s lives. Cornell University Press. (pp. 112–115).
- Hempel, Carl G., & Oppenheim, P. (1948). “Studies in the Logic of Explanation”. Philosophy of Science, 2(15), 135–175. Retrieved from https://www.jstor.org/stable/185169
- Hempel, Carl Gustav. (2001). The Philosophy of Carl G. Hempel: Studies in science, explanation, and rationality ( J. H. Fetzer, Ed.). Oxford New York: Oxford University Press.
- King, R. D., Rowland, J., Oliver, S. G., Young, M., Aubrey, W., Byrne, E., … Clare, A. (2009). “The Automation of Science”. Science, 324(5923), 85–89. https://doi.org/10.1126/ science.1165620
- Knorr Cetina, K. (1999). Epistemic cultures: How the sciences make knowledge. Harvard University Press. (pp. 183–185).
- Lamola, M. J. (2022). “On the robosphere: A philosophical explication of the sociotechnical status of social robots”. International Journal of Social Robotics, 14, 1199– 1209. https://doi.org/10.1007/s12369-021-00840-3.
- Latour, B. (1987). Science in action: How to follow scientists and engineers through society. Harvard University Press. (pp. 70–72).
- Lipton, Z. C. (2018). “The Mythos of Model Interpretability: In machine learning, the concept of interpretability is both important and slippery”. Queue, 16(3), 31–57. https://doi.org/10.1145/3236386.3241340
- Longino, H. E. (2020). Science as Social Knowledge: Values and Objectivity in Scientific Inquiry. Princeton University Press. https://doi.org/10.2307/j.ctvx5wbfz
- OECD. (2023). Artificial intelligence in science: Challenges, opportunities and the future of research. OECD Publishing. https://doi.org/10.1787/a8d820bd-en (pp. 10–15).
- Putnam, H. (1964). “Robots: Machines or artificially created life?”. The Journal of Philosophy, 61(21), 668–691. https://doi.org/10.2307/2023045 (pp. 668–670).
- Winner, L. (1980). “Do Artifacts Have Politics?”. Daedalus, 109(1), 121–136. JSTOR. Retrieved from http://www.jstor.org/stable/20024652
- World Economic Forum. (2020). This robot scientist conducted experiments by itself during COVID-19 lockdown. https://www.weforum.org/agenda/2020/08/robot-scientistautonomous-chemistry-university-of-liverpool.
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Konular | Bilim Felsefesi, Teknoloji Felsefesi |
| Bölüm | Araştırma Makalesi |
| Yazarlar | |
| Yayımlanma Tarihi | 27 Haziran 2025 |
| Gönderilme Tarihi | 24 Nisan 2025 |
| Kabul Tarihi | 27 Mayıs 2025 |
| Yayımlandığı Sayı | Yıl 2025 Sayı: 27 |
