From 6a35e4c1331e72cb40f90b650af4e8780535fc97 Mon Sep 17 00:00:00 2001
From: brutzman <brutzman@nps.edu>
Date: Sun, 20 Mar 2022 08:11:32 -0700
Subject: [PATCH] AAAI SSS 2022 abstracts

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 EthicalControl.html | 96 +++++++++++++++++++++++++++++++++++++++------
 1 file changed, 84 insertions(+), 12 deletions(-)

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@@ -178,9 +178,10 @@ more-effective supervision of operations involving lethal or life-saving force.
                     <p>
                         <!-- Unicode Character 'BOOKMARK' (U+1F516) https://www.fileformat.info/info/unicode/char/1f516/index.htm -->
                         <a href="#AAAISpringSymposium2022EthicalComputingMetrics">&#128278;</a>
-                       <a href="https://aaai.org/Symposia/Spring/sss22symposia.php#ss06" target="AAAI2022">Ethical Computing: Metrics for Measuring AI's Proficiency and Competency for Ethical Reasoning</a>
+                        <a href="https://aaai.org/Symposia/Spring/sss22symposia.php#ss06" target="AAAI2022">Ethical Computing: Metrics for Measuring AI's Proficiency and Competency for Ethical Reasoning</a>
                     </p>
                     <p>
+                        <i>Symposium workshop overview.</i>
                         The prolific deployment of Artificial Intelligence (AI) across different applications have introduced novel challenges 
                         for AI developers and researchers. AI is permeating decision making for the masses: from self-driving automobiles, 
                         to financial loan approval, to military applications. Ethical decisions have largely been made by humans 
@@ -188,34 +189,105 @@ more-effective supervision of operations involving lethal or life-saving force.
                         With AI making decisions, those ethical responsibilities are now being pushed to AI designers 
                         who may be far-removed from how, where, and when the ethical dilemma occurs. 
                         Such systems may deploy global "ethical" rules with unanticipated or unintended local effects or vice versa.
-</p>
-                    <p>
                         While explainability is desirable, it is likely not sufficient for creating "ethical AI", 
                         i.e. machines that can make ethical decisions. These systems will require the 
                         invention of new evaluation techniques around the AI's proficiency and competency in its own ethical reasoning. Using traditional software and system testing methods on ethical AI algorithms may not be feasible because what is considered "ethical" often consists of judgements made within situational contexts. The question of what is ethical has been studied for centuries. This symposium invites interdisciplinary methods for characterizing and measuring ethical decisions as applied to ethical AI.
                     </p>
                     <p>
-                        One of nine workshops for
+                        This event is one of nine workshops for
                         <a href="https://aaai.org/Symposia/Spring/sss22symposia.php" target="AAAI2022">Association for Advancement of Artificial Intelligence (AAAI) Spring Symposium</a>, 
                         21-23&nbsp;March&nbsp;2022,
-                        organized by our collaborating colleagues at Raytheon.
+                        and is organized by our collaborating colleagues at Raytheon.
+                        Work building on these capabilities is presented in three sessions.
                        (<a href="https://sites.google.com/view/aaai-ethicalcomputingapproach/schedule" target="_blank">schedule</a>)
                     </p>
                    <ul>
                        <li>
-                           <a href="documentation/papers/SSS-22_paper_117_TieredApproachEthicalAIEvaluationMetrics.pdf" target="_blank">A Tiered Approach for Ethical AI Evaluation Metrics</a>,
-                           <br />
-                           Peggy Wu, Brett Israelsen, Kunal Srivastava, Hsin-Fu "Sinker" Wu, and Robert Grabowski.
+                           <p>
+                            <a href="documentation/papers/SSS-22_paper_117_TieredApproachEthicalAIEvaluationMetrics.pdf" target="_blank">A Tiered Approach for Ethical AI Evaluation Metrics</a>,
+                            <br />
+                            Peggy Wu, Brett Israelsen, Kunal Srivastava, Hsin-Fu "Sinker" Wu, and Robert Grabowski.
+                           </p>
+                           <p>
+                               <i>Abstract.</i>
+Advances in machine learning are enabling autonomy to operate 
+in environments of increasing complexity, including 
+scenarios with ethical concerns. For many Artificial Intelligence (AI) 
+systems, decisions are driven by the goal to maximize reward. 
+Policies may contain unintended consequences 
+known as reward hacking. The AI is optimizing within the 
+constraints defined by the domain and goals and does not 
+have the capability to distinguish between benign and 
+negative consequences beyond specifications. This paper 
+describes an ongoing effort to develop an application-agnostic
+framework for AI systems to simulate actions, characterize 
+potential outcomes, and perform introspection to articulate 
+the motivations for action. Such a framework provides the 
+foundational work for higher-level ethical reasoning using 
+consequential and deontological ethics than other approaches
+in AI ethics. This enables metrics from consequential ethics 
+to be used to assign ethical value of actions based on outcomes. 
+Simultaneously, metrics from deontological ethics 
+can be applied to evaluate the universality of its motivations.
+A Trolley Problem -inspired maritime search-and-rescue scenario 
+is used to operationalize and demonstrate this framework.
+                           </p>
                        </li>
                        <li>
-                          <a href="documentation/papers/SSS-22_paper_118_DoctrineEthicsCompliantAutonomyOntologicalFramework.pdf" target="_blank">Doctrine and Ethics Compliant Autonomy Using An Ontological Framework</a>,
-                           <br />
-                           Don Brutzman,  Curt Blais, Hsin-Fu "Sinker" Wu, Richard Markeloff and Carl Andersen.
+                           <p>
+                            <a href="documentation/papers/SSS-22_paper_118_DoctrineEthicsCompliantAutonomyOntologicalFramework.pdf" target="_blank">Doctrine and Ethics Compliant Autonomy Using An Ontological Framework</a>,
+                            <br />
+                            Don Brutzman,  Curt Blais, Hsin-Fu "Sinker" Wu, Richard Markeloff, and Carl Andersen.
+                           </p>
+                           <p>
+                               <i>Abstract.</i>
+Ensuring ethical robot behavior requires complex representations 
+and methodologies designed to guarantee it. Our approach extends 
+frameworks already used by the U.S. military
+to ensure human ethical and doctrinal behavior by human beings. 
+These have built in advantages of being able to express
+complex plans and constraints, yet remaining intelligible to
+humans, a requirement for ethical responsibility and liability. 
+To extend the framework to machines, mission constructs
+are expressed using an Autonomous Vehicle Command Language (AVCL) 
+expressing mission actions and outcomes that
+can readily be translated to runnable source code in several
+programming languages. Missions written in AVCL can be
+validated via translation to an RDF/OWL Mission Execution
+Ontology (MEO) supporting queried proofs of ethical correctness. 
+MEO ensures that missions are both semantically
+valid and compliant with ethical constraints. These technologies 
+implement a simulation, testing, and certification regime
+that can serve as a foundation for human authority over and
+trust in robots capable of lethal force.
+                           </p>
+                           <p>
+                               This paper is dedicated to the memory of Rich Markeloff who made substantial contributions
+                               towards our understanding, adaptation and usage of advanced Semantic Web capabilities
+                               supporting ethical control of unmanned systems.
+                           </p>
                        </li>
                        <li>
+                           <p>
                            <a href="documentation/papers/SSS-22_paper_122_MeaningfulMetricsDemonstratingEthicalSupervision.pdf" target="_blank">Meaningful Metrics for Demonstrating Ethical Supervision of Unmanned Systems</a>,
                            <br />
                            Don Brutzman and Curt Blais.
+                           </p>
+                           <p>
+                               <i>Abstract.</i>
+Metrics for AI are important, as illustrated by the workshop topics of interest. We note that 
+commonplace gaps in applied AI derive from “Here are the measurements we know how to take” which are too 
+easily over-extrapolated into conclusions of interest. In other words, such precise metrics are necessary and 
+appealing but may not broadly apply to general situations. We assert that necessary subsequent questions are 
+“How do we define meaningful objectives and outcomes for a current unmanned system,” “How do we measure 
+those characteristics that indicate expected success/failure,” and “Once we can measure meaningful results, 
+how do we assemble exemplars into test suites that confirm successful completion across ongoing system life
+cycles?”
+                           </p>
+                           <p>
+This discussion session seeks to find common threads among all workshop contributions that may help advance
+progress on these fundamental challenges.
+                           </p>
                        </li>
                    </ul>
                 </td>
@@ -1392,7 +1464,7 @@ more-effective supervision of operations involving lethal or life-saving force.
         </p>
         
         <p>
-            Updated: 19 March 2022
+            Updated: 20 March 2022
         </p>
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