Critique of Modern BI as Autonomous Intelligence
Report 2 of 2 · 2/26/2026
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Web sources61
- 1Self-Service Business Intelligence 2024 – Dresner Advisory Services
portal.dresneradvisory.com
- 2Evolving Business Intelligence and Analytics – Research Report 2024
sapinsider.org
- 3G2’s AI in Data Integration Report: 2026 Vendor Insights
learn.g2.com
- 4The Autonomous AI Problem No One Wants to Discuss
alteryx.com
- 5Exploring automation bias in human–AI collaboration: a review and implications for explainable AI
link.springer.com
- 6Exploring automation bias in human–AI collaboration: a review and implications for explainable AI
iris.unict.it
- 7CSET AI Safety and Automation Bias — cset.georgetown.edu
cset.georgetown.edu
- 8Measuring and mitigating overreliance is necessary for building human-compatible AI
arxiv.org
- 9Examining the limitations of AI in business and the need for human insights using Interpretive Structural Modelling
sciencedirect.com
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sloanreview.mit.edu
- 11When combinations of humans and AI are useful: A systematic review and meta-analysis
nature.com
- 12hai ai index report 2024 smaller2 — hai.stanford.edu
hai.stanford.edu
- 13Business intelligence
en.wikipedia.org
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investopedia.com
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powerbi.microsoft.com
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techtarget.com
- 17Tackling Trust, Risk and Security in AI Models
gartner.com
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- 192025 Gartner® Market Guide for AI TRiSM Report UK | Proofpoint UK
proofpoint.com
- 20The state of AI in early 2024: Gen AI adoption spikes and starts to generate value
mckinsey.com
- 21Building AI trust: The key role of explainability
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- 23The state of AI: How organizations are rewiring to capture value
- 24NeurIPS Poster Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers
neurips.cc
- 2529753d93c5fc11167567e5df800308ae Paper Conference — proceedings.neurips.cc
proceedings.neurips.cc
- 26Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers
nips.cc
- 27Computer Science > Machine Learning
- 28Causal AI at KDD 2024 — Why Companies That Won’t Jump on the Causal Train Now Will Have a Harder Time Competing in 2025 and Beyond
medium.com
- 29Commentary: Implications of causality in artificial intelligence. Why Causal AI is easier said than done
frontiersin.org
- 30pdf — openreview.net
openreview.net
- 31Causal AI: Transforming the Future of Asset Management Today
tredence.com
- 32Automation Bias in AI-Decision Support: Results from an Empirical Study
pubmed.ncbi.nlm.nih.gov
- 33Exploring the risks of automation bias in healthcare artificial intelligence applications: A Bowtie analysis
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- 35Find the Good. Seek the Unity: A Hidden Markov Model of Human-AI Delegation Dynamics 1
Open Access
misq.umn.edu
- 36Find the Good. Seek the Unity: A Hidden Markov Model of Human-AI Delegation Dynamics
- 37Shared Autonomy with IDA: Interventional Diffusion Assistance
- 38e7ba43ea2a7f94d86e69de761e178792 Paper Conference — proceedings.neurips.cc
- 39NeurIPS Poster Shared Autonomy with IDA: Interventional Diffusion Assistance
- 40A theoretical case-study of Scalable Oversight in Hierarchical Reinforcement Learning | OpenReview
- 41ICML Poster Causal Discovery via Conditional Independence Testing with Proxy Variables
icml.cc
- 42Score-Based Causal Discovery of Latent Variable Causal Models
proceedings.mlr.press
- 43Causal Discovery over High-Dimensional Structured Hypothesis Spaces with Causal Graph Partitioning
- 44Automation bias
- 45Automation bias: a systematic review of frequency, effect mediators, and mitigators
ncbi.nlm.nih.gov
- 46Results Of Forrester’s Automation Survey, 2024
forrester.com
- 47AI-Infused (Augmented) Business Intelligence Further Democratizes Enterprise Data
- 48Automation Bias: What It Is And How To Overcome It
forbes.com
- 49The Business Intelligence Platforms Landscape, Q4 2024
- 50When combinations of humans and AI are useful: A systematic review and meta-analysis
- 51s41562 024 02024 1 — resources1972.s3.us-east-2.amazonaws.com
resources1972.s3.us-east-2.amazonaws.com
- 52When combinations of humans and AI are useful: A systematic review and meta-analysis
pmc.ncbi.nlm.nih.gov
- 53When humans and AI work best together — and when each is better alone
mitsloan.mit.edu
- 54When combinations of humans and AI are useful: A systematic review and meta-analysis
- 55Center for Security and Emerging Technology
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govwhitepapers.com
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hai-production.s3.amazonaws.com
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omnitech.my
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icthealth.org
- 61pdf — openreview.net