added pdf of lara's paper

content/publication/kirfel2023anticipating.md

@@ -12,11 +12,11 @@ authors = ["L. Kirfel","R. J. MacCoun","T. Icard","T. Gerstenberg"]
 publication_types = ["3"]
 publication_short = "_AI Meets Moral Philosophy and Moral Psychology Workshop (NeurIPS 2023)_"
 publication = "Kirfel L., MacCoun R. J., Icard T., Gerstenberg T. (2023). Anticipating the risks and benefits of counterfactual world simulation models. In _AI Meets Moral Philosophy and Moral Psychology Workshop (NeurIPS 2023)_."
-abstract = "This paper examines the transformative potential of Counterfactual World Simulation Models (CWSMs). A CWSM uses multi-modal evidence, such as the CCTV footage of a road accident, to build a high-fidelity 3D reconstruction of what happened. It can answer causal questions, such as whether the accident happened because the driver was speeding, by simulating what would have happened in relevant counterfactual situations. We argue for a normative and ethical framework that guides and constrains the simulation of counterfactuals. We address the challenge of ensuring fidelity in reconstructions while simultaneously preventing stereotype perpetuation during counterfactual simulations. We anticipate different modes of how users will interact with CWSMs and discuss how their outputs may be presented. Finally, we address the prospective applications of CWSMs in the legal domain, recognizing both their potential to revolutionize legal proceedings as well as the ethical concerns they engender. Sketching a new genre of AI, this paper seeks to illuminate the path forward for responsible and effective use of CWSMs."
+abstract = "This paper examines the transformative potential of Counterfactual World Simulation Models (CWSMs). CWSMs use pieces of multi-modal evidence, such as the CCTV footage or sound recordings of a road accident, to build a high-fidelity 3D reconstruction of the scene. They can also answer causal questions, such as whether the accident happened because the driver was speeding, by simulating what would have happened in relevant counterfactual situations. CWSMs will enhance our capacity to envision alternate realities and investigate the outcomes of counterfactual alterations to how events unfold. This also, however, raises questions about what alternative scenarios we should be considering and what to do with that knowledge. We present a normative and ethical framework that guides and constrains the simulation of counterfactuals. We address the challenge of ensuring fidelity in reconstructions while simultaneously preventing stereotype perpetuation during counterfactual simulations. We anticipate different modes of how users will interact with CWSMs and discuss how their outputs may be presented. Finally, we address the prospective applications of CWSMs in the legal domain, recognizing both their potential to revolutionize legal proceedings as well as the ethical concerns they engender. Anticipating a new type of AI, this paper seeks to illuminate a path forward for responsible and effective use of CWSMs."
 image_preview = ""
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 projects = []
-#url_pdf = "papers/kirfel2023anticipating.pdf"
+url_pdf = "papers/kirfel2023anticipating.pdf"
 url_preprint = ""
 url_code = ""
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docs/bibtex/cic_papers.bib

@@ -1,7 +1,7 @@
 %% This BibTeX bibliography file was created using BibDesk.
 %% https://bibdesk.sourceforge.io/
 
-%% Created for Tobias Gerstenberg at 2023-10-30 18:45:54 -0700 
+%% Created for Tobias Gerstenberg at 2023-11-20 10:18:20 -0800 
 
 
 %% Saved with string encoding Unicode (UTF-8) 
@@ -18,11 +18,11 @@ @inproceedings{nie2023moca
 	year = {2023}}
 
 @inproceedings{kirfel2023anticipating,
-	abstract = {This paper examines the transformative potential of Counterfactual World Simulation Models (CWSMs). A CWSM uses multi-modal evidence, such as the CCTV footage of a road accident, to build a high-fidelity 3D reconstruction of what happened. It can answer causal questions, such as whether the accident happened because the driver was speeding, by simulating what would have happened in relevant counterfactual situations. We argue for a normative and ethical framework that guides and constrains the simulation of counterfactuals. We address the challenge of ensuring fidelity in reconstructions while simultaneously preventing stereotype perpetuation during counterfactual simulations. We anticipate different modes of how users will interact with CWSMs and discuss how their outputs may be presented. Finally, we address the prospective applications of CWSMs in the legal domain, recognizing both their potential to revolutionize legal proceedings as well as the ethical concerns they engender. Sketching a new genre of AI, this paper seeks to illuminate the path forward for responsible and effective use of CWSMs.},
+	abstract = {This paper examines the transformative potential of Counterfactual World Simulation Models (CWSMs). CWSMs use pieces of multi-modal evidence, such as the CCTV footage or sound recordings of a road accident, to build a high-fidelity 3D reconstruction of the scene. They can also answer causal questions, such as whether the accident happened because the driver was speeding, by simulating what would have happened in relevant counterfactual situations. CWSMs will enhance our capacity to envision alternate realities and investigate the outcomes of counterfactual alterations to how events unfold. This also, however, raises questions about what alternative scenarios we should be considering and what to do with that knowledge. We present a normative and ethical framework that guides and constrains the simulation of counterfactuals. We address the challenge of ensuring fidelity in reconstructions while simultaneously preventing stereotype perpetuation during counterfactual simulations. We anticipate different modes of how users will interact with CWSMs and discuss how their outputs may be presented. Finally, we address the prospective applications of CWSMs in the legal domain, recognizing both their potential to revolutionize legal proceedings as well as the ethical concerns they engender. Anticipating a new type of AI, this paper seeks to illuminate a path forward for responsible and effective use of CWSMs.},
 	author = {Lara Kirfel and Robert J. MacCoun and Thomas Icard and Tobias Gerstenberg},
 	booktitle = {{AI Meets Moral Philosophy and Moral Psychology Workshop (NeurIPS 2023)}},
 	date-added = {2023-10-30 18:20:41 -0700},
-	date-modified = {2023-10-30 18:20:50 -0700},
+	date-modified = {2023-11-20 10:18:20 -0800},
 	title = {Anticipating the risks and benefits of counterfactual world simulation models},
 	year = {2023}}
 

docs/member/tobias_gerstenberg/index.html

@@ -371,6 +371,10 @@ <h2 id="publications">Publications</h2>
 
 
 
+<a class="btn btn-outline-primary my-1 mr-1 btn-sm" href="https://cicl.stanford.edu/papers/kirfel2023anticipating.pdf" target="_blank" rel="noopener">
+  PDF
+</a>
+
 
 
 

docs/publication/index.html

@@ -1567,6 +1567,10 @@ <h1>Publications</h1>
 
 
 
+<a class="btn btn-outline-primary my-1 mr-1 btn-sm" href="https://cicl.stanford.edu/papers/kirfel2023anticipating.pdf" target="_blank" rel="noopener">
+  PDF
+</a>
+
 
 
 

docs/publication/kirfel2023anticipating/index.html

@@ -15,7 +15,7 @@
 
 
 
-  <meta name="description" content="This paper examines the transformative potential of Counterfactual World Simulation Models (CWSMs). A CWSM uses multi-modal evidence, such as the CCTV footage of a road accident, to build a high-fidelity 3D reconstruction of what happened. It can answer causal questions, such as whether the accident happened because the driver was speeding, by simulating what would have happened in relevant counterfactual situations. We argue for a normative and ethical framework that guides and constrains the simulation of counterfactuals. We address the challenge of ensuring fidelity in reconstructions while simultaneously preventing stereotype perpetuation during counterfactual simulations. We anticipate different modes of how users will interact with CWSMs and discuss how their outputs may be presented. Finally, we address the prospective applications of CWSMs in the legal domain, recognizing both their potential to revolutionize legal proceedings as well as the ethical concerns they engender. Sketching a new genre of AI, this paper seeks to illuminate the path forward for responsible and effective use of CWSMs.">
+  <meta name="description" content="This paper examines the transformative potential of Counterfactual World Simulation Models (CWSMs). CWSMs use pieces of multi-modal evidence, such as the CCTV footage or sound recordings of a road accident, to build a high-fidelity 3D reconstruction of the scene. They can also answer causal questions, such as whether the accident happened because the driver was speeding, by simulating what would have happened in relevant counterfactual situations. CWSMs will enhance our capacity to envision alternate realities and investigate the outcomes of counterfactual alterations to how events unfold. This also, however, raises questions about what alternative scenarios we should be considering and what to do with that knowledge. We present a normative and ethical framework that guides and constrains the simulation of counterfactuals. We address the challenge of ensuring fidelity in reconstructions while simultaneously preventing stereotype perpetuation during counterfactual simulations. We anticipate different modes of how users will interact with CWSMs and discuss how their outputs may be presented. Finally, we address the prospective applications of CWSMs in the legal domain, recognizing both their potential to revolutionize legal proceedings as well as the ethical concerns they engender. Anticipating a new type of AI, this paper seeks to illuminate a path forward for responsible and effective use of CWSMs.">
 
 
   <link rel="alternate" hreflang="en-us" href="https://cicl.stanford.edu/publication/kirfel2023anticipating/">
@@ -108,7 +108,7 @@
   <meta property="og:site_name" content="Causality in Cognition Lab">
   <meta property="og:url" content="https://cicl.stanford.edu/publication/kirfel2023anticipating/">
   <meta property="og:title" content="Anticipating the risks and benefits of counterfactual world simulation models | Causality in Cognition Lab">
-  <meta property="og:description" content="This paper examines the transformative potential of Counterfactual World Simulation Models (CWSMs). A CWSM uses multi-modal evidence, such as the CCTV footage of a road accident, to build a high-fidelity 3D reconstruction of what happened. It can answer causal questions, such as whether the accident happened because the driver was speeding, by simulating what would have happened in relevant counterfactual situations. We argue for a normative and ethical framework that guides and constrains the simulation of counterfactuals. We address the challenge of ensuring fidelity in reconstructions while simultaneously preventing stereotype perpetuation during counterfactual simulations. We anticipate different modes of how users will interact with CWSMs and discuss how their outputs may be presented. Finally, we address the prospective applications of CWSMs in the legal domain, recognizing both their potential to revolutionize legal proceedings as well as the ethical concerns they engender. Sketching a new genre of AI, this paper seeks to illuminate the path forward for responsible and effective use of CWSMs.">
+  <meta property="og:description" content="This paper examines the transformative potential of Counterfactual World Simulation Models (CWSMs). CWSMs use pieces of multi-modal evidence, such as the CCTV footage or sound recordings of a road accident, to build a high-fidelity 3D reconstruction of the scene. They can also answer causal questions, such as whether the accident happened because the driver was speeding, by simulating what would have happened in relevant counterfactual situations. CWSMs will enhance our capacity to envision alternate realities and investigate the outcomes of counterfactual alterations to how events unfold. This also, however, raises questions about what alternative scenarios we should be considering and what to do with that knowledge. We present a normative and ethical framework that guides and constrains the simulation of counterfactuals. We address the challenge of ensuring fidelity in reconstructions while simultaneously preventing stereotype perpetuation during counterfactual simulations. We anticipate different modes of how users will interact with CWSMs and discuss how their outputs may be presented. Finally, we address the prospective applications of CWSMs in the legal domain, recognizing both their potential to revolutionize legal proceedings as well as the ethical concerns they engender. Anticipating a new type of AI, this paper seeks to illuminate a path forward for responsible and effective use of CWSMs.">
   <meta property="og:locale" content="en-us">
 
   <meta property="article:published_time" content="2023-10-30T00:00:00&#43;00:00">
@@ -252,7 +252,7 @@ <h1 itemprop="name" class ="title-text">Anticipating the risks and benefits of c
 
 
     <h3>Abstract</h3>
-    <p class="pub-abstract" itemprop="text">This paper examines the transformative potential of Counterfactual World Simulation Models (CWSMs). A CWSM uses multi-modal evidence, such as the CCTV footage of a road accident, to build a high-fidelity 3D reconstruction of what happened. It can answer causal questions, such as whether the accident happened because the driver was speeding, by simulating what would have happened in relevant counterfactual situations. We argue for a normative and ethical framework that guides and constrains the simulation of counterfactuals. We address the challenge of ensuring fidelity in reconstructions while simultaneously preventing stereotype perpetuation during counterfactual simulations. We anticipate different modes of how users will interact with CWSMs and discuss how their outputs may be presented. Finally, we address the prospective applications of CWSMs in the legal domain, recognizing both their potential to revolutionize legal proceedings as well as the ethical concerns they engender. Sketching a new genre of AI, this paper seeks to illuminate the path forward for responsible and effective use of CWSMs.</p>
+    <p class="pub-abstract" itemprop="text">This paper examines the transformative potential of Counterfactual World Simulation Models (CWSMs). CWSMs use pieces of multi-modal evidence, such as the CCTV footage or sound recordings of a road accident, to build a high-fidelity 3D reconstruction of the scene. They can also answer causal questions, such as whether the accident happened because the driver was speeding, by simulating what would have happened in relevant counterfactual situations. CWSMs will enhance our capacity to envision alternate realities and investigate the outcomes of counterfactual alterations to how events unfold. This also, however, raises questions about what alternative scenarios we should be considering and what to do with that knowledge. We present a normative and ethical framework that guides and constrains the simulation of counterfactuals. We address the challenge of ensuring fidelity in reconstructions while simultaneously preventing stereotype perpetuation during counterfactual simulations. We anticipate different modes of how users will interact with CWSMs and discuss how their outputs may be presented. Finally, we address the prospective applications of CWSMs in the legal domain, recognizing both their potential to revolutionize legal proceedings as well as the ethical concerns they engender. Anticipating a new type of AI, this paper seeks to illuminate a path forward for responsible and effective use of CWSMs.</p>
 
 
 
@@ -316,6 +316,10 @@ <h3>Abstract</h3>
 
 
 
+<a class="btn btn-outline-primary my-1 mr-1" href="https://cicl.stanford.edu/papers/kirfel2023anticipating.pdf" target="_blank" rel="noopener">
+  PDF
+</a>
+
 
 
 

docs/publication_types/3/index.html

@@ -242,7 +242,7 @@ <h1 class="pt-3">3</h1>
     <h2><a href="https://cicl.stanford.edu/publication/kirfel2023anticipating/">Anticipating the risks and benefits of counterfactual world simulation models</a></h2>
     <div class="article-style">
 
-      This paper examines the transformative potential of Counterfactual World Simulation Models (CWSMs). A CWSM uses multi-modal evidence, such as the CCTV footage of a road accident, to build a high-fidelity 3D reconstruction of what happened. It can …
+      This paper examines the transformative potential of Counterfactual World Simulation Models (CWSMs). CWSMs use pieces of multi-modal evidence, such as the CCTV footage or sound recordings of a road accident, to build a high-fidelity 3D reconstruction …
 
     </div>
   </div>

static/bibtex/cic_papers.bib

@@ -1,7 +1,7 @@
 %% This BibTeX bibliography file was created using BibDesk.
 %% https://bibdesk.sourceforge.io/
 
-%% Created for Tobias Gerstenberg at 2023-10-30 18:45:54 -0700 
+%% Created for Tobias Gerstenberg at 2023-11-20 10:18:20 -0800 
 
 
 %% Saved with string encoding Unicode (UTF-8) 
@@ -18,11 +18,11 @@ @inproceedings{nie2023moca
 	year = {2023}}
 
 @inproceedings{kirfel2023anticipating,
-	abstract = {This paper examines the transformative potential of Counterfactual World Simulation Models (CWSMs). A CWSM uses multi-modal evidence, such as the CCTV footage of a road accident, to build a high-fidelity 3D reconstruction of what happened. It can answer causal questions, such as whether the accident happened because the driver was speeding, by simulating what would have happened in relevant counterfactual situations. We argue for a normative and ethical framework that guides and constrains the simulation of counterfactuals. We address the challenge of ensuring fidelity in reconstructions while simultaneously preventing stereotype perpetuation during counterfactual simulations. We anticipate different modes of how users will interact with CWSMs and discuss how their outputs may be presented. Finally, we address the prospective applications of CWSMs in the legal domain, recognizing both their potential to revolutionize legal proceedings as well as the ethical concerns they engender. Sketching a new genre of AI, this paper seeks to illuminate the path forward for responsible and effective use of CWSMs.},
+	abstract = {This paper examines the transformative potential of Counterfactual World Simulation Models (CWSMs). CWSMs use pieces of multi-modal evidence, such as the CCTV footage or sound recordings of a road accident, to build a high-fidelity 3D reconstruction of the scene. They can also answer causal questions, such as whether the accident happened because the driver was speeding, by simulating what would have happened in relevant counterfactual situations. CWSMs will enhance our capacity to envision alternate realities and investigate the outcomes of counterfactual alterations to how events unfold. This also, however, raises questions about what alternative scenarios we should be considering and what to do with that knowledge. We present a normative and ethical framework that guides and constrains the simulation of counterfactuals. We address the challenge of ensuring fidelity in reconstructions while simultaneously preventing stereotype perpetuation during counterfactual simulations. We anticipate different modes of how users will interact with CWSMs and discuss how their outputs may be presented. Finally, we address the prospective applications of CWSMs in the legal domain, recognizing both their potential to revolutionize legal proceedings as well as the ethical concerns they engender. Anticipating a new type of AI, this paper seeks to illuminate a path forward for responsible and effective use of CWSMs.},
 	author = {Lara Kirfel and Robert J. MacCoun and Thomas Icard and Tobias Gerstenberg},
 	booktitle = {{AI Meets Moral Philosophy and Moral Psychology Workshop (NeurIPS 2023)}},
 	date-added = {2023-10-30 18:20:41 -0700},
-	date-modified = {2023-10-30 18:20:50 -0700},
+	date-modified = {2023-11-20 10:18:20 -0800},
 	title = {Anticipating the risks and benefits of counterfactual world simulation models},
 	year = {2023}}