Month: January 2025

Winners and losers of generative AI: Early Evidence of Shifts in Freelancer Demand

Ole Teutloff, Johanna Einsiedler, Otto Kässi, Fabian Braesemann,  Pamela Mishkin,  R. Maria del Rio-Chanona

Journal of Economic Behavior & Organization

We examine how ChatGPT has changed the demand for freelancers in jobs where generative AI tools can act as substitutes or complements to human labor. Using BERTopic we partition job postings from a leading online freelancing platform into 116 fine-grained skill clusters and with GPT-4o we classify them as substitutable, complementary or unaffected by LLMs. Our analysis reveals that labor demand increased after the launch of ChatGPT, but only in skill clusters that were complementary to or unaffected by the AI tool. In contrast, demand for substitutable skills, such as writing and translation, decreased by 20–50% relative to the counterfactual trend, with the sharpest decline observed for short-term (1-3 week) jobs. Within complementary skill clusters, the results are mixed: demand for machine learning programming grew by 24%, and demand for AI-powered chatbot development nearly tripled, while demand for novice workers declined in general. This result suggests a shift toward more specialized expertise for freelancers rather than uniform growth across all complementary areas.

Read the full article at: www.sciencedirect.com

Complex Systems Seminar Series | Portland State University

The Complex Systems Seminar Series covers a wide range of topics, providing an opportunity for presenters to share and attendees to become exposed to the latest research from different fields and disciplines. 

Agent-based simulation, artificial intelligence, artificial life, genetic algorithms, machine learning, neural networks, signal processing, social networks, system dynamics, and science itself are just a few of the many diverse topics that have been presented, all in an informal environment where questions and discussion are encouraged.

Schedule at: www.pdx.edu

Machine Learning in Information and Communications Technology: A Survey

Elias Dritsas and Maria Trigka

Information 2025, 16(1), 8;

The rapid growth of data and the increasing complexity of modern networks have driven the demand for intelligent solutions in the information and communications technology (ICT) domain. Machine learning (ML) has emerged as a powerful tool, enabling more adaptive, efficient, and scalable systems in this field. This article presents a comprehensive survey on the application of ML techniques in ICT, covering key areas such as network optimization, resource allocation, anomaly detection, and security. Specifically, we review the effectiveness of different ML models across ICT subdomains and assess how ML integration enhances crucial performance metrics, including operational efficiency, scalability, and security. Lastly, we highlight the challenges and future directions that are critical for the continued advancement of ML-driven innovations in ICT.

Read the full article at: www.mdpi.com

Systematic comparison of gender inequality in scientific rankings across disciplines

Ana Maria Jaramillo, Mariana Macedo, Marcos Oliveira, Fariba Karimi, Ronaldo Menezes

The participation of women in academia has increased in the last few decades across many fields (e.g., Computer Science, History, Medicine). However, this increase in the participation of women has not been the same at all career stages. Here, we study how gender participation within different fields is related to gender representation in top-ranking positions in productivity (number of papers), research impact (number of citations), and co-authorship networks (degree of connectivity). We analyzed over 80 million papers published from 1975 to 2020 in 19 academic fields. Our findings reveal that women remain a minority in all 19 fields, with physics, geology, and mathematics having the lowest percentage of papers authored by women at 14% and psychology having the largest percentage at 39%. Women are significantly underrepresented in top-ranking positions (top 10% or higher) across all fields and metrics (productivity, citations, and degree), indicating that it remains challenging for early researchers (especially women) to reach top-ranking positions, as our results reveal the rankings to be rigid over time. Finally, we show that in most fields, women and men with comparable productivity levels and career age tend to attain different levels of citations, where women tend to benefit more from co-authorships, while men tend to benefit more from productivity, especially in pSTEMs. Our findings highlight that while the participation of women has risen in some fields, they remain under-represented in top-ranking positions. Greater gender participation at entry levels often helps representation, but stronger interventions are still needed to achieve long-lasting careers for women and their participation in top-ranking positions.

Read the full article at: arxiv.org

Thoughts and thinkers: On the complementarity between objects and processes

Chris Fields, Michael Levin

Physics of Life Reviews

• An information-theoretic approach to biology renders “objects” and “processes” interchangable at every scale.
• Morphogenesis is a process of memory construction at every scale.
• Life depends on lateral information flows between its component lineages at every scale.
• Viewing living systems as multi-scale competency architectures forefronts communication via scale-appropriate interfaces, as opposed to manipulation of components, as a strategy for both therapuetic intervention and bioengineering.

Read the full article at: www.sciencedirect.com