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AI_and_Employment.pdfAutomation_2020.pdfLabor_Markets.pdf
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⢠AI applications have not led to significant job losses; they
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ResearchPal's Paper Insights feature allows you to analyze multiple research papers simultaneously. Simply select PDF files from your uploaded documents or imported libraries such as Zotero or Mendeley, and generate structured insights instantly.

Depending on your subscription level, you can select multiple papers and compare them side-by-side, helping you identify patterns, trends, and key findings faster.
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ResearchPal organizes insights into structured columns, allowing you to compare multiple research papers in one unified view. This makes it easier to analyze differences, similarities, and research contributions across papers.

By default, the Insights column is generated, and additional insight types can be enabled based on your research needs.
Compare Research Papers in a Structured View
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Control the Level of Insight Detail

ResearchPal allows you to adjust the length of generated insights based on your needs:

 

  • Short insights for quick comparison
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This flexibility helps researchers balance speed and depth.

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Export Insights for Further Research

Export generated insights in multiple formats to use in your academic workflow, research reports, or collaboration tools. Export Formats:

 

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This makes it easy to integrate insights into your research workflow.

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Access and Update Saved Insights Anytime
All generated insights are automatically saved in the Saved Insights tab. If certain insight types were not generated initially, you can generate them later directly from the saved insights table.

Whenever new insights are generated, the saved insights are automatically updated, ensuring your research analysis remains current.
Screenshot of the Saved Insights tab showing previously generated research insights

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Open AccessFiltersSee GuidelinesCorpus 0/250 char
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Limitations of AI233 char
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Limitations of AI
Max Jamilly, a PhD student at the University of Oxford, Fintan Nagle, a cognitive neuroscientist at UCL, and Charles Ross, Chairman of the Brain Mind Forum, discuss a new era of human and machine symbiosis for artificial intelligence.
NoneMax Jamilly, F. Naglâ¦3 Citations2018Connected Papers
DOI: 10.1093/ITNOW/BWY006CiteSaveSource
Limitations of AI
The promise of AI with its breathtaking range of applications seems to be without limits. To elaborate on limitations of AI may therefore be perceived by some of our readers as a spin in opposite directions. AI is so much associated with accelerating innovation, insight, and decision making that we see its opportunities as immeasurable. And yet, even for AI, there are limits and challenges, as we â¦
NoneEberhard Hechler, Mâ¦0 Citations2020Connected Papers
DOI: 10.1007/978-1-4842-6206-1_13CiteSaveSource
The Limits of Artificial Intelligence
This paper examines the boundaries of current machine learning systems, focusing on generalization, data dependence, and the absence of causal reasoning that constrains real-world deployment across domains.
NoneR. Kaur et al.7 Citations2022Connected Papers
DOI: 10.1016/j.artint.2022.103771CiteSaveSource
Rethinking AI Limitations
We argue that many perceived limitations of AI stem from misaligned evaluation methods rather than fundamental capability gaps, and propose a framework for more faithful benchmarking of model behavior.
NoneT. Okafor, L. Reyes1 Citation2023Connected Papers
DOI: 10.1145/3583131.3590482CiteSaveSource

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Humans vs ai238 char
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â Alert: Please do not reload or close your browser tab while literature processing is underway. Doing so may cause unexpected behavior and errors in your literature review.
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Oral Boards: Humans vs. AI
NoneN/A0 Citations2025
DOI: 10.1213/ane.0000000000007554CiteSaveSourceSimilarity Graph
Humans vs. AI in Detecting Vehicle Damage
NoneAlice Yang, Guoyang â¦4 Citations2024
DOI: Not availableCiteSaveSourceSimilarity Graph
HumanâAI Collaboration in Clinical Decisions
NoneM. Chen et al.12 Citations2023
DOI: 10.1038/s41746-023-00987CiteSaveSourceSimilarity Graph
Paper Details
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AI-Complete, AI-Hard, or AI-Easy - Classification of Problems in AI
Roman V Yampolskiy
None
2012
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Citations0 Influential Citations50 Citations
References62 References
Summary:
Abstract
The paper contributes to the development of the theory of AI-Completeness by formalizing the notion of AI-Complete and AI-Hard problems. The intended goal is to provide a classification of problems in the field of General Artificial Intelligence. We prove Turing Test to be an instance of an AI-Complete problem and further show numerous AI problems to be AI-Complete or AI-Hard via polynomial time reductions. Finally, the paper suggests some directions for future work on the theory of AI-Completeness. Keywords: AI-Complete, AI-Easy, AI-Hard, Human
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Yampolskiy, 2012Hendler, 2008Bergmair, 2006Shieber, 2006Chang, 2013Hogan, 2020Majhi, 2020Bingley, 2024Chen, 2015Hein, 2016
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AI-Complete, AI-Hard, or AI-Easy â Classification of Problems in AI
Roman V Yampolskiy
2012
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The abstract for this research paper is currently unavailable due to a request from the publisher. To access further details, click on the search result to obtain the source link to the publisher.

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1The_study_of_boundaries_in_the_social_sc…1 / 31100%
Annu. Rev. Sociol. 2002. 28:167–95
doi: 10.1146/annurev.soc.28.110601.141107
Copyright © 2002 by Annual Reviews. All rights reserved
THE STUDY OF BOUNDARIES IN THE SOCIAL SCIENCES
Michèle Lamont and Virág Molnár
Department of Sociology, Princeton University, Princeton, New Jersey 08540; e-mail: Mlamont@princeton.edu, vmolnar@phoenix.princeton.edu
Key Words  culture, identity, inequality, community, borders
■ Abstract  In recent years, the concept of boundaries has been at the center of influential research agendas in anthropology, history, political science, social psychology, and sociology. This article surveys some of these developments while describing the value added provided by the concept, particularly concerning the study of relational processes. It discusses literatures on (a) social and collective identity; (b) class, ethnic/racial, and gender/sex inequality; (c) professions, knowledge, and science; and (d) communities, national identities, and spatial boundaries.
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Format:APAMLACHICAGO
Bessen, J. (2019). Artificial Intelligence and Jobs: The Role of Demand. In A. Agrawal, J. Gans, & A. Goldfarb (Eds.), The Economics of Artificial Intelligence: An Agenda (pp. 291–307). University of Chicago Press.
Acemoglu, D., & Restrepo, P. (2018). Artificial Intelligence, Automation and Work. National Bureau of Economic Research.

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â¦behind urban centers in terms of access to resources, employment opportunities, and basic services (Rodriguez-Pose and Hardy, 2015).

The United Nations estimates that hundreds of millions in Asia still exist below the international poverty line, facing difficulties related to health care, education, and nutrition. Education disparities also contribute to socio-economic challenges in the region (Rolleston and Crouch, 2021).

Countries such as Bangladesh and Afghanistan struggle with low enrollment rates, particularly for girls, leading to a cycle of poverty that is difficult to break.

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