Difference between revisions of "Other terms"
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<h2>AI systems</h2> | <h2>AI systems</h2> | ||
The notion of an “intelligent system” is neither defined precisely nor demarcated sharply from other systems, artifacts, or technical devices. Instead, the perception of what is judged to be intelligent changes with progress and exposure to such a system. Broadly speaking, an intelligent system is commonly understood as a computational system – such as a search engine, an online shopping assistant, a chat bot, or a cleaning robot – that leverages concepts, tools, and techniques from artificial intelligence in order to establish capabilities that are commonly attributed to humans while (still) being less typical of other soft- and hardware systems. Most notably, these capabilities let an AI system learn from experience and adapt to specific environmental conditions. As a consequence, an intelligent system exhibits a certain degree of autonomy, and its behavior is not completely prespecified. Importantly, intelligent systems are able to interact with humans or other systems through various modalities, for example, textual, visual, acoustic, or haptic signals. Whereas we share contemporary definitions of intelligent systems, we specifically focus on the abilities of AI systems to learn not only from prespecified data but also through interacting with humans. | "The notion of an “intelligent system” is neither defined precisely nor demarcated sharply from other systems, artifacts, or technical devices. Instead, the perception of what is judged to be intelligent changes with progress and exposure to such a system. Broadly speaking, an intelligent system is commonly understood as a computational system – such as a search engine, an online shopping assistant, a chat bot, or a cleaning robot – that leverages concepts, tools, and techniques from artificial intelligence in order to establish capabilities that are commonly attributed to humans while (still) being less typical of other soft- and hardware systems. Most notably, these capabilities let an AI system learn from experience and adapt to specific environmental conditions. As a consequence, an intelligent system exhibits a certain degree of autonomy, and its behavior is not completely prespecified. Importantly, intelligent systems are able to interact with humans or other systems through various modalities, for example, textual, visual, acoustic, or haptic signals. Whereas we share contemporary definitions of intelligent systems, we specifically focus on the abilities of AI systems to learn not only from prespecified data but also through interacting with humans." <ref name="TRR_318_proposal">TRR 318 Proposal</ref> | ||
<h2>Co-construction</h2> | <h2>Co-construction</h2> | ||
In the realm of explanations, "co-construction refers to an interactive and iterative process of negotiating both the explanandum and the form of understanding for explanations. It is a process that is performed mutually by sequentially building on, refining, and modifying the interaction: Each partner elaborates upon the other partner’s last contribution. The processes of scaffolding and monitoring guide this elaboration and direct it toward a specific form of understanding. In effect, what is achieved is the participation of both partners in moving toward a goal. Whereas the co-construction of an explanation takes place on the microlevel of an unfolding interaction and can thus be accessed directly, the process is modulated crucially on the macrolevel of the interaction."<ref name="TRR_318_proposal"/> | |||
<h2>Explainee</h2> | <h2>Explainee</h2> | ||
The | "The agent on the receiving end of an explanation."<ref name="TRR_318_proposal"/> | ||
When a teacher explains a concept in class, she is the explainer and the students are the explainees. | |||
<h2>Explainer</h2> | <h2>Explainer</h2> | ||
The | "The agent who steers an explanation forward"<ref name="TRR_318_proposal"/> | ||
<h2>Explanandum</h2> | <h2>Explanandum</h2> | ||
The entity (event, phenomenon) that is the subject of an explanation | "The entity (event, phenomenon) that is the subject of an explanation"<ref name="TRR_318_proposal"/> | ||
<h2>Explanans</h2> | <h2>Explanans</h2> | ||
The (verbal) way that an explanation can be expressed and co-constructed by both partners | "The (verbal) way that an explanation can be expressed and co-constructed by both partners"<ref name="TRR_318_proposal"/> | ||
<h2>Monitoring</h2> | <h2>Monitoring</h2> | ||
Monitoring is a multimodal process where observed outcomes are compared to what was predicted<ref name="Pickering_ Garrod_2013">Pickering MJ, Garrod S. An integrated theory of language production and comprehension. Behav Brain Sci. 2013 Aug;36(4):329-47. doi: 10.1017/S0140525X12001495. Epub 2013 Jun 24. PMID: 23789620.</ref>. Partners use speech, gestures, and nonverbal cues to track joint task progress. The explainer assesses the explainee's understanding, determining if their explanation is effective or requires refinement. Conversely, the explainee monitors the explainer, accepting the necessary level of detail for a specific explanation.<ref name="TRR_318_proposal"/> | |||
<h2>Scaffolding</h2> | <h2>Scaffolding</h2> | ||
In developmental literature, scaffolding refers to the way an expert provides guidance to a learner within a learning process by increasing or reducing the level of assistance in accordance with the partner’s performance. In our approach, we transfer the term from the area of learning to understanding. In accordance with the idea that understanding is constructed by both partners, both partners can scaffold each other—that is, provide the other partner with the information needed to arrive at a joint construction of the explanandum and the desired form of understanding. Together with the process of monitoring, it is not only a form of guidance but also supervision, and both together aid the active participation of both partners. | "In developmental literature, scaffolding refers to the way an expert provides guidance to a learner within a learning process by increasing or reducing the level of assistance in accordance with the partner’s performance. In our approach, we transfer the term from the area of learning to understanding. In accordance with the idea that understanding is constructed by both partners, both partners can scaffold each other—that is, provide the other partner with the information needed to arrive at a joint construction of the explanandum and the desired form of understanding. Together with the process of monitoring, it is not only a form of guidance but also supervision, and both together aid the active participation of both partners."<ref name="TRR_318_proposal"/> | ||
<h2>Understanding</h2> | <h2>Understanding</h2> | ||
Whereas in the current debate on explainable systems (XAI), understanding refers to the problem of receiving “enough information” (Miller 2019, p. 11), in our approach, understanding is linked to what is relevant for the explainee. To account for variations in the progress of and the varying goals of explanations, we will differentiate between practices of enabling and comprehension. With enabling, we refer to explanations in the context of choosing or performing an action. Comprehension, in contrast, accounts for a reflexive awareness that may lead to a conceptual framework for a phenomenon that goes beyond what is immediately perceivable. We expect further differentiations that will be explored in the individual projects. | "Whereas in the current debate on explainable systems (XAI), understanding refers to the problem of receiving “enough information” (Miller 2019, p. 11), in our approach, understanding is linked to what is relevant for the explainee. To account for variations in the progress of and the varying goals of explanations, we will differentiate between practices of enabling and comprehension. With enabling, we refer to explanations in the context of choosing or performing an action. Comprehension, in contrast, accounts for a reflexive awareness that may lead to a conceptual framework for a phenomenon that goes beyond what is immediately perceivable. We expect further differentiations that will be explored in the individual projects."<ref name="TRR_318_proposal"/> | ||
<h2>Social-practice</h2> | <h2>Social-practice</h2> | ||
Social practice determines the social relations and power structures in a given situation and thereby provides a specific (normative) background for the way interaction will play out in order to ‘place’ the explanation appropriately, and finally how that explanation will be interpreted. Social practice is a product of our actions with respect to each other that often has both social consequences and social presuppositions. The consequences on the one hand and the presuppositions on the other hand speak to the two timescales that constitute a social practice: In terms of consequences, every explaining process re-establishes the relevant social practice; in terms of presuppositions, in turn, the experience of an explaining process will confirm or make a new contribution to our expectations, roles, and partner models in relation to this particular social practice. | "Social practice determines the social relations and power structures in a given situation and thereby provides a specific (normative) background for the way interaction will play out in order to ‘place’ the explanation appropriately, and finally how that explanation will be interpreted. Social practice is a product of our actions with respect to each other that often has both social consequences and social presuppositions. The consequences on the one hand and the presuppositions on the other hand speak to the two timescales that constitute a social practice: In terms of consequences, every explaining process re-establishes the relevant social practice; in terms of presuppositions, in turn, the experience of an explaining process will confirm or make a new contribution to our expectations, roles, and partner models in relation to this particular social practice."<ref name="TRR_318_proposal"/> | ||
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<h2>dyad</h2> | <h2>dyad</h2> | ||
two individuals (such as husband and wife) maintaining a sociologically significant relationship <ref>https://www.merriam-webster.com/dictionary/dyad</ref> | |||
<h2>partner-model</h2> | <h2>partner-model</h2> | ||
a partner model is a main resource is for ‘placing’ explanations and contains knowledge and assumptions about the explainee with regard to her/his dialogical role, general characteristics, or even this specific person | a partner model is a main resource is for ‘placing’ explanations and contains knowledge and assumptions about the explainee with regard to her/his dialogical role, general characteristics, or even this specific person <ref name="TRR_318_proposal"/> | ||
<h2>Obligation</h2> | <h2>Obligation</h2> | ||
Obligations represent what an agent should do, according to some set of norms. The notion of obligation has been studied for many centuries, and its formal aspects are examined using Deontic Logic. | Obligations represent what an agent should do, according to some set of norms. The notion of obligation has been studied for many centuries, and its formal aspects are examined using Deontic Logic.<ref name="traum1994discourse">Traum, D. R., & Allen, J. F. (1994). Discourse obligations in dialogue processing. arXiv preprint cmp-lg/9407011.</ref> | ||
<h2>obligor</h2> | <h2>obligor</h2> | ||
one who is bound by a legal obligation | one who is bound by a legal obligation <ref>https://www.merriam-webster.com/dictionary/obligor</ref> | ||
<h2>obligee</h2> | <h2>obligee</h2> | ||
one to whom another is obligated (as by a contract). specifically : one who is protected by a surety bond | one to whom another is obligated (as by a contract). specifically : one who is protected by a surety bond <ref>https://www.merriam-webster.com/dictionary/obligee</ref> | ||
<h2> interlocutor </h2> | <h2> interlocutor </h2> | ||
one who takes part in dialogue or conversation | one who takes part in dialogue or conversation <ref>https://www.merriam-webster.com/dictionary/interlocutor</ref> | ||
<h2> reappraisal </h2> | <h2> reappraisal </h2> | ||
re-interpreting or re-analyzing the emotional situation and/or goals | "re-interpreting or re-analyzing the emotional situation and/or goals" <ref name="TRR_318_proposal"/> | ||
<h2> Persuasion </h2> | <h2> Persuasion </h2> | ||
Persuasion can be seen as a further strategy to achieve a decision or behavior that is congruent with logical argumentation and not influenced by emotional processes. | "Persuasion can be seen as a further strategy to achieve a decision or behavior that is congruent with logical argumentation and not influenced by emotional processes."<ref name="TRR_318_proposal"/> | ||
<h2> feedback signals </h2> | <h2> feedback signals </h2> | ||
Feedback signals are generally (i) short (i.e., consist of minimal verbal/vocal expressions), (ii) locally adapted to their prosodic context (i.e., the speaker’s utterance) by being more similar in pitch to their immediate surrounding than regular utterances, or (iii) taking place in the visual modality, for example as head gestures or facial expressions. | "Feedback signals are generally (i) short (i.e., consist of minimal verbal/vocal expressions), (ii) locally adapted to their prosodic context (i.e., the speaker’s utterance) by being more similar in pitch to their immediate surrounding than regular utterances, or (iii) taking place in the visual modality, for example as head gestures or facial expressions." <ref name="buschmeier2018attentive">Buschmeier, H. (2018). Attentive speaking. From listener feedback to interactive adaptation. | ||
ISO 690 | |||
</ref> | |||
<h2>verbal-feedback</h2> | <h2>verbal-feedback</h2> | ||
"Feedback is considered ‘verbal/vocal’, if it is spoken, i.e., produced as a speech sound in the vocal tract of a listener. Examples of such feedback found in the alico-corpus are genau (‘exactly’), ja (‘yes’), mhm (‘uh-huh’), and m."<ref name="buschmeier2018attentive"/> | |||
< | |||
<h2> fact </h2> | <h2> fact </h2> | ||
that what happened | that what happened <ref name="wang2019designing">Wang, D., Yang, Q., Abdul, A., & Lim, B. Y. (2019, May). Designing theory-driven user-centric explainable AI. In Proceedings of the 2019 CHI conference on human factors in computing systems (pp. 1-15).</ref> | ||
<h2> foil </h2> | <h2> foil </h2> | ||
that what is expected or plausible to happen | that what is expected or plausible to happen<ref name="wang2019designing"/> | ||
<h2> causal-explanation </h2> | <h2> causal-explanation </h2> | ||
refers to an explanation that is focused on selected causes relevant to interpreting the observation with respect to existing knowledge. | "refers to an explanation that is focused on selected causes relevant to interpreting the observation with respect to existing knowledge."<ref name="wang2019designing"/> | ||
<h2> EXPLAINING-WHY </h2> | <h2> EXPLAINING-WHY </h2> | ||
It is a semantic type of explanation which explicates how a complex matter comes into being (e.g., explaining natural phenomena by reference to physical principles, or explaining a person’s action by explicating possible motives. | It is a semantic type of explanation which explicates how a complex matter comes into being (e.g., explaining natural phenomena by reference to physical principles, or explaining a person’s action by explicating possible motives.<ref name="TRR_318_proposal"/> | ||
<h2> EXPLAINING-HOW </h2> | <h2> EXPLAINING-HOW </h2> | ||
It is a semantic type of explanation which outlines procedural knowledge about processes and coordinations of actions in order to achieve a specific goal. | It is a semantic type of explanation which outlines procedural knowledge about processes and coordinations of actions in order to achieve a specific goal.<ref name="TRR_318_proposal"/> | ||
<h2> EXPLAINING-WHAT </h2> | <h2> EXPLAINING-WHAT </h2> | ||
It is a semantic type of explanation which describes, for example, the meaning of a term or a proverb. We consider these distinctions to be useful for describing ways of explaining technical artifacts because they reflect their intrinsic duality. | It is a semantic type of explanation which describes, for example, the meaning of a term or a proverb. We consider these distinctions to be useful for describing ways of explaining technical artifacts because they reflect their intrinsic duality.<ref name="TRR_318_proposal"/> | ||
<h2> Deontic logic </h2> | <h2> Deontic logic </h2> | ||
Deontic logic is the field of philosophical logic that is concerned with obligation, permission, and related concepts. Alternatively, a deontic logic is a formal system that attempts to capture the essential logical features of these concepts. | Deontic logic is the field of philosophical logic that is concerned with obligation, permission, and related concepts. Alternatively, a deontic logic is a formal system that attempts to capture the essential logical features of these concepts. <ref>Stanford Encyclopedia of Philosophy https://plato.stanford.edu/entries/logic-deontic/</ref> | ||
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<h2>dialog-act</h2> | <h2>dialog-act</h2> | ||
In linguistics and in particular in natural language understanding, a dialog act is an utterance, in the context of a conversational dialog, that serves a function in the dialog. Types of dialog acts include a question, a statement, or a request for action. Dialog acts are a type of speech act. | In linguistics and in particular in natural language understanding, a dialog act is an utterance, in the context of a conversational dialog, that serves a function in the dialog. Types of dialog acts include a question, a statement, or a request for action. Dialog acts are a type of speech act. | ||
--> | |||
==Notes== | |||
<references /> | |||
Latest revision as of 09:05, 29 August 2023
AI systems
"The notion of an “intelligent system” is neither defined precisely nor demarcated sharply from other systems, artifacts, or technical devices. Instead, the perception of what is judged to be intelligent changes with progress and exposure to such a system. Broadly speaking, an intelligent system is commonly understood as a computational system – such as a search engine, an online shopping assistant, a chat bot, or a cleaning robot – that leverages concepts, tools, and techniques from artificial intelligence in order to establish capabilities that are commonly attributed to humans while (still) being less typical of other soft- and hardware systems. Most notably, these capabilities let an AI system learn from experience and adapt to specific environmental conditions. As a consequence, an intelligent system exhibits a certain degree of autonomy, and its behavior is not completely prespecified. Importantly, intelligent systems are able to interact with humans or other systems through various modalities, for example, textual, visual, acoustic, or haptic signals. Whereas we share contemporary definitions of intelligent systems, we specifically focus on the abilities of AI systems to learn not only from prespecified data but also through interacting with humans." [1]
Co-construction
In the realm of explanations, "co-construction refers to an interactive and iterative process of negotiating both the explanandum and the form of understanding for explanations. It is a process that is performed mutually by sequentially building on, refining, and modifying the interaction: Each partner elaborates upon the other partner’s last contribution. The processes of scaffolding and monitoring guide this elaboration and direct it toward a specific form of understanding. In effect, what is achieved is the participation of both partners in moving toward a goal. Whereas the co-construction of an explanation takes place on the microlevel of an unfolding interaction and can thus be accessed directly, the process is modulated crucially on the macrolevel of the interaction."[1]
Explainee
"The agent on the receiving end of an explanation."[1]
When a teacher explains a concept in class, she is the explainer and the students are the explainees.
Explainer
"The agent who steers an explanation forward"[1]
Explanandum
"The entity (event, phenomenon) that is the subject of an explanation"[1]
Explanans
"The (verbal) way that an explanation can be expressed and co-constructed by both partners"[1]
Monitoring
Monitoring is a multimodal process where observed outcomes are compared to what was predicted[2]. Partners use speech, gestures, and nonverbal cues to track joint task progress. The explainer assesses the explainee's understanding, determining if their explanation is effective or requires refinement. Conversely, the explainee monitors the explainer, accepting the necessary level of detail for a specific explanation.[1]
Scaffolding
"In developmental literature, scaffolding refers to the way an expert provides guidance to a learner within a learning process by increasing or reducing the level of assistance in accordance with the partner’s performance. In our approach, we transfer the term from the area of learning to understanding. In accordance with the idea that understanding is constructed by both partners, both partners can scaffold each other—that is, provide the other partner with the information needed to arrive at a joint construction of the explanandum and the desired form of understanding. Together with the process of monitoring, it is not only a form of guidance but also supervision, and both together aid the active participation of both partners."[1]
Understanding
"Whereas in the current debate on explainable systems (XAI), understanding refers to the problem of receiving “enough information” (Miller 2019, p. 11), in our approach, understanding is linked to what is relevant for the explainee. To account for variations in the progress of and the varying goals of explanations, we will differentiate between practices of enabling and comprehension. With enabling, we refer to explanations in the context of choosing or performing an action. Comprehension, in contrast, accounts for a reflexive awareness that may lead to a conceptual framework for a phenomenon that goes beyond what is immediately perceivable. We expect further differentiations that will be explored in the individual projects."[1]
Social-practice
"Social practice determines the social relations and power structures in a given situation and thereby provides a specific (normative) background for the way interaction will play out in order to ‘place’ the explanation appropriately, and finally how that explanation will be interpreted. Social practice is a product of our actions with respect to each other that often has both social consequences and social presuppositions. The consequences on the one hand and the presuppositions on the other hand speak to the two timescales that constitute a social practice: In terms of consequences, every explaining process re-establishes the relevant social practice; in terms of presuppositions, in turn, the experience of an explaining process will confirm or make a new contribution to our expectations, roles, and partner models in relation to this particular social practice."[1]
dyad
two individuals (such as husband and wife) maintaining a sociologically significant relationship [3]
partner-model
a partner model is a main resource is for ‘placing’ explanations and contains knowledge and assumptions about the explainee with regard to her/his dialogical role, general characteristics, or even this specific person [1]
Obligation
Obligations represent what an agent should do, according to some set of norms. The notion of obligation has been studied for many centuries, and its formal aspects are examined using Deontic Logic.[4]
obligor
one who is bound by a legal obligation [5]
obligee
one to whom another is obligated (as by a contract). specifically : one who is protected by a surety bond [6]
interlocutor
one who takes part in dialogue or conversation [7]
reappraisal
"re-interpreting or re-analyzing the emotional situation and/or goals" [1]
Persuasion
"Persuasion can be seen as a further strategy to achieve a decision or behavior that is congruent with logical argumentation and not influenced by emotional processes."[1]
feedback signals
"Feedback signals are generally (i) short (i.e., consist of minimal verbal/vocal expressions), (ii) locally adapted to their prosodic context (i.e., the speaker’s utterance) by being more similar in pitch to their immediate surrounding than regular utterances, or (iii) taking place in the visual modality, for example as head gestures or facial expressions." [8]
verbal-feedback
"Feedback is considered ‘verbal/vocal’, if it is spoken, i.e., produced as a speech sound in the vocal tract of a listener. Examples of such feedback found in the alico-corpus are genau (‘exactly’), ja (‘yes’), mhm (‘uh-huh’), and m."[8]
fact
that what happened [9]
foil
that what is expected or plausible to happen[9]
causal-explanation
"refers to an explanation that is focused on selected causes relevant to interpreting the observation with respect to existing knowledge."[9]
EXPLAINING-WHY
It is a semantic type of explanation which explicates how a complex matter comes into being (e.g., explaining natural phenomena by reference to physical principles, or explaining a person’s action by explicating possible motives.[1]
EXPLAINING-HOW
It is a semantic type of explanation which outlines procedural knowledge about processes and coordinations of actions in order to achieve a specific goal.[1]
EXPLAINING-WHAT
It is a semantic type of explanation which describes, for example, the meaning of a term or a proverb. We consider these distinctions to be useful for describing ways of explaining technical artifacts because they reflect their intrinsic duality.[1]
Deontic logic
Deontic logic is the field of philosophical logic that is concerned with obligation, permission, and related concepts. Alternatively, a deontic logic is a formal system that attempts to capture the essential logical features of these concepts. [10]
Notes
- ↑ 1.00 1.01 1.02 1.03 1.04 1.05 1.06 1.07 1.08 1.09 1.10 1.11 1.12 1.13 1.14 1.15 TRR 318 Proposal
- ↑ Pickering MJ, Garrod S. An integrated theory of language production and comprehension. Behav Brain Sci. 2013 Aug;36(4):329-47. doi: 10.1017/S0140525X12001495. Epub 2013 Jun 24. PMID: 23789620.
- ↑ https://www.merriam-webster.com/dictionary/dyad
- ↑ Traum, D. R., & Allen, J. F. (1994). Discourse obligations in dialogue processing. arXiv preprint cmp-lg/9407011.
- ↑ https://www.merriam-webster.com/dictionary/obligor
- ↑ https://www.merriam-webster.com/dictionary/obligee
- ↑ https://www.merriam-webster.com/dictionary/interlocutor
- ↑ 8.0 8.1 Buschmeier, H. (2018). Attentive speaking. From listener feedback to interactive adaptation. ISO 690
- ↑ 9.0 9.1 9.2 Wang, D., Yang, Q., Abdul, A., & Lim, B. Y. (2019, May). Designing theory-driven user-centric explainable AI. In Proceedings of the 2019 CHI conference on human factors in computing systems (pp. 1-15).
- ↑ Stanford Encyclopedia of Philosophy https://plato.stanford.edu/entries/logic-deontic/