User:WikiSysop - Revision history

WikiSysop at 17:30, 23 November 2024

2024-11-23T17:30:24Z

← Older revision		Revision as of 13:30, 23 November 2024
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	As outlined below, professions such as civil engineering have been successful in acting in the face of uncertainty lies in the profession's ability to reduce a broad variety of uncertainties into a series of increasingly smaller and crucially bounded subsets that can be managed. These are called 'risks. More recently, this process has evolved, and individual disciplines such as Civil Engineering (CE) have developed their knowledge and models to perform risk analysis. Risk is also taught as a distinct discipline and specialty practice within civil engineering. Still, it has some unique features that set it apart from other more classical practices within CE. As such, it is one of the first of some very specialized CE practices that use knowledge about civil engineering knowledge, or meta-knowledge. Other examples of civil engineering metaknowledge are project controls and quality controls.		As outlined below, professions such as civil engineering have been successful in acting in the face of uncertainty lies in the profession's ability to reduce a broad variety of uncertainties into a series of increasingly smaller and crucially bounded subsets that can be managed. These are called 'risks. More recently, this process has evolved, and individual disciplines such as Civil Engineering (CE) have developed their knowledge and models to perform risk analysis. Risk is also taught as a distinct discipline and specialty practice within civil engineering. Still, it has some unique features that set it apart from other more classical practices within CE. As such, it is one of the first of some very specialized CE practices that use knowledge about civil engineering knowledge, or meta-knowledge. Other examples of civil engineering metaknowledge are project controls and quality controls.
	==Semantic, Epistemic and Logical frameworks==		==Semantic, Epistemic and Logical frameworks==
	The semantic, epistemic, and logical frameworks for uncertainty and risk have several dimensions and layers of logical frameworks. The semantics problems include interchangeable usages for risk and uncertainty and hazard, uncertain and imperfect, and a lack of definitional material or context. The semantical scheme for this article will be to proceed from the distinction between certainty and uncertainty through marginal refinements and reductions of uncertainty up to the point of causal uncertainties. Beyond this point of semantics will be the logic frameworks or the subject of taxonomies of professional knowledge. First, it is about simple, testable phenomena, and then, it moves on to complex taxonomy schemes for artificially constructed phenomena or engineering projects. ~~[[#Notes\|~~Note ~~2]]~~		The semantic, epistemic, and logical frameworks for uncertainty and risk have several dimensions and layers of logical frameworks. The semantics problems include interchangeable usages for risk and uncertainty and hazard, uncertain and imperfect, and a lack of definitional material or context. The semantical scheme for this article will be to proceed from the distinction between certainty and uncertainty through marginal refinements and reductions of uncertainty up to the point of causal uncertainties. Beyond this point of semantics will be the logic frameworks or the subject of taxonomies of professional knowledge. First, it is about simple, testable phenomena, and then, it moves on to complex taxonomy schemes for artificially constructed phenomena or engineering projects. <ref group="Note"> TBD </ref>
	==Semantics framework==		==Semantics framework==
	===Certainty and Uncertainty===		===Certainty and Uncertainty===

WikiSysop at 17:28, 23 November 2024

2024-11-23T17:28:21Z

← Older revision		Revision as of 13:28, 23 November 2024
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	over the centuries has been to reshape and re-frame our understanding and conception of uncertainty from one of		over the centuries has been to reshape and re-frame our understanding and conception of uncertainty from one of
	complete unknowing and simple acceptance as our fate in life to one of management (cf"Against the Gods"		complete unknowing and simple acceptance as our fate in life to one of management (cf"Against the Gods"
	concept in Bernstein's book [21). All the knowledge professions and disciplines have struggled with managing uncertainty, for it is impossible to manage unbounded uncertainty. [Note 1] <br>		concept in Bernstein's book [21).
			: ''' All the knowledge professions and disciplines have struggled with managing uncertainty, for it is impossible to manage unbounded uncertainty.''' <ref group="Note"> See McDaniels et al. 2004 for an extensive discussion and bibliography on the historical development of Risk Analysis and some key milestones in risk analysis in the 20th century.</ref>
	As outlined below, professions such as civil engineering have been successful in acting in the face of uncertainty lies in the profession's ability to reduce a broad variety of uncertainties into a series of increasingly smaller and crucially bounded subsets that can be managed. These are called 'risks. More recently, this process has evolved, and individual disciplines such as Civil Engineering (CE) have developed their knowledge and models to perform risk analysis. Risk is also taught as a distinct discipline and specialty practice within civil engineering. Still, it has some unique features that set it apart from other more classical practices within CE. As such, it is one of the first of some very specialized CE practices that use knowledge about civil engineering knowledge, or meta-knowledge. Other examples of civil engineering metaknowledge are project controls and quality controls.		As outlined below, professions such as civil engineering have been successful in acting in the face of uncertainty lies in the profession's ability to reduce a broad variety of uncertainties into a series of increasingly smaller and crucially bounded subsets that can be managed. These are called 'risks. More recently, this process has evolved, and individual disciplines such as Civil Engineering (CE) have developed their knowledge and models to perform risk analysis. Risk is also taught as a distinct discipline and specialty practice within civil engineering. Still, it has some unique features that set it apart from other more classical practices within CE. As such, it is one of the first of some very specialized CE practices that use knowledge about civil engineering knowledge, or meta-knowledge. Other examples of civil engineering metaknowledge are project controls and quality controls.
	==Semantic, Epistemic and Logical frameworks==		==Semantic, Epistemic and Logical frameworks==
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	[[#top\|Top of current page]]		[[#top\|Top of current page]]
	==Notes==		==Notes==
	~~# See McDaniels et al. 2004 for an extensive discussion and bibliography on the historical development of Risk Analysis and some key milestones in the 20th century.~~		<references group="Note"/>

	# Open item		# Open item
	# The Merriam-Webster dictionary defines uncertainty:		# The Merriam-Webster dictionary defines uncertainty:
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	</ol>		</ol>
	==References==		==References==
			<references />
	~~==References==~~

	~~==Notes==~~

	~~==References==~~
	'''Certainty''' has been defined as "an epistemic property" of knowledge in all its forms and the state of our beliefs about that knowledge. <ref name="Note3"/> Certainty about any belief about knowledge in any form implies that it is not subject to doubt or skepticism. This immunity to criticism can be dogmatically based, emphasizing the importance of a propositional-based sense of truth over experiential, sensory perceptions. <ref name="Note4"/>		'''Certainty''' has been defined as "an epistemic property" of knowledge in all its forms and the state of our beliefs about that knowledge. <ref name="Note3"/> Certainty about any belief about knowledge in any form implies that it is not subject to doubt or skepticism. This immunity to criticism can be dogmatically based, emphasizing the importance of a propositional-based sense of truth over experiential, sensory perceptions. <ref name="Note4"/>
	<ref name="Note3">Certainty defined as an epistemic property in ''Fox, D. (Year). Title of the Book. Publisher.''</ref>		<ref name="Note3">Certainty defined as an epistemic property in ''Fox, D. (Year). Title of the Book. Publisher.''</ref>
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	<ref name="Reference5">[5]</ref></ref>		<ref name="Reference5">[5]</ref></ref>
	<references />		<references />

	~~==References==~~

	~~==References==~~

	~~==Notes==~~

	==References==		==References==

WikiSysop: /* Notes */

2024-11-23T17:04:11Z

Notes

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WikiSysop at 16:47, 23 November 2024

2024-11-23T16:47:10Z

← Older revision		Revision as of 12:47, 23 November 2024
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	* Knowledge how ( or "[https://en.wikipedia.org/wiki/Procedural_knowledge know-how]"), and		* Knowledge how ( or "[https://en.wikipedia.org/wiki/Procedural_knowledge know-how]"), and
	* [https://en.wikipedia.org/wiki/Knowledge_by_acquaintance Knowledge by acquaintance].		* [https://en.wikipedia.org/wiki/Knowledge_by_acquaintance Knowledge by acquaintance].
	'''Certainty''' has been defined as "an epistemic property" of knowledge in all its forms and the state of our beliefs about that knowledge. <ref name="Note3"/> Certainty about any belief about knowledge in any form implies that it is not subject to doubt or skepticism. This immunity to criticism can be dogmatically based, emphasizing the importance of a propositional-based sense of truth over experiential, sensory perceptions. <ref name="Note4"/>

	The demarcation line between dogmatic and non-dogmatic beliefs lies in the presence and recognition of specific criteria and information that would make the believer change their beliefs. There is an underlying requirement for an empirical framework of testability and falsification to recognize this, to limit dogmatism. For example, one could argue that they would change their minds if God asked them to do so. Similarly, one could construct a concept of epistemic as opposed to dogmatic belief certainty as the ability to know anything that one chooses to know and can be known or inherent omniscience.		The demarcation line between dogmatic and non-dogmatic beliefs lies in the presence and recognition of specific criteria and information that would make the believer change their beliefs. There is an underlying requirement for an empirical framework of testability and falsification to recognize this, to limit dogmatism. For example, one could argue that they would change their minds if God asked them to do so. Similarly, one could construct a concept of epistemic as opposed to dogmatic belief certainty as the ability to know anything that one chooses to know and can be known or inherent omniscience.
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	<references group="note" />		<references group="note" />
	~~<ref name="Note3">Certainty defined as an epistemic property in ''Fox, D. (Year). Title of the Book. Publisher.''</ref>~~
	~~<ref name="Note4">The importance of propositional truth over experiential perception as discussed in ''Fox, D. (Year). Title of the Book. Publisher.''</ref>~~
	'''Uncertainty''', on the other hand, arises immediately in the slightest amount of doubt or criticism. <ref name="Note3">[Note 3]</ref> Similarly, a general definition of uncertainty could be given as "...any departure from the unachievable goal of complete determinism." <ref name="Reference5">[5]</ref> Reasoning under uncertainty is very different than performing the same under certainty. In reasoning under certainty, one has complete knowledge and deduces without doubt and equally important, without limitation, thereby concluding free from error. Reasoning under uncertainty, one works in a state of incomplete, inconsistent, and limited knowledge; doubts cloud any statements or assertions and thereby taint any deductions/inferences resulting in the potential for error. <ref name="Note4">[Note 4]</ref>
	:'''Knowledge professions reason in a state of incomplete, inconsistent and limited knowledge with doubts that cloud any statements or assertions and taint any deductions/inferences resulting in the potential for error.'''		:'''Knowledge professions reason in a state of incomplete, inconsistent and limited knowledge with doubts that cloud any statements or assertions and taint any deductions/inferences resulting in the potential for error.'''
	:''' It is also important to note the semantical and logical correlation between 'reasoning under uncertainty' or 'acting in the face of uncertainty' with the 'potential for' or 'presence of' error. The presence of uncertainty is invariably linked to the potential presence of error.''' The [https://en.wikipedia.org/wiki/Contingency_(philosophy) contingent] nature of uncertainty logically implies the contingent nature of error.		:''' It is also important to note the semantical and logical correlation between 'reasoning under uncertainty' or 'acting in the face of uncertainty' with the 'potential for' or 'presence of' error. The presence of uncertainty is invariably linked to the potential presence of error.''' The [https://en.wikipedia.org/wiki/Contingency_(philosophy) contingent] nature of uncertainty logically implies the contingent nature of error.
	:'''Knowledge Professions use error as a proxy for uncertainty such that within discipline knowledge frameworks, uncertainty can be managed.''' The rationale for this belief is that error can be reliably described, quantified, explained, and ultimately reduced in ways that uncertainty cannot.		:'''Knowledge Professions use error as a proxy for uncertainty such that within discipline knowledge frameworks, uncertainty can be managed.''' The rationale for this belief is that error can be reliably described, quantified, explained, and ultimately reduced in ways that uncertainty cannot.

	~~<references>~~
	~~<ref name="Note3">[Note 3]</ref>~~
	~~<ref name="Reference5">[5]</ref>~~
	~~<ref name="Note4">[Note 4]</ref>~~
	</references>		</references>

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	Engineering and Economics, for example, simulate finite elements of perfect knowledge or information, heavily bounded with assumptions and a range of applications. By doing so, these professions reduce the bounds and variability of uncertainty and thereby manage it. Using these hybrid models to acquire knowledge takes place in an economy (regulated or institutional) and environment (transparent and structured), which puts pressure on the various professions to recognize and use qualitative and quantitative knowledge better to reduce uncertainties in their activities. The challenges in this reflect the nature of the profession's or discipline's knowledge (e.g., scientific, engineering, or medical), the policies and structure of the relevant professional knowledge bodies, process objectives and constraints, and "the elusive demands of politics." [6] One common theme runs through all of these efforts to address the presence of uncertainty in professional activities. <br>		Engineering and Economics, for example, simulate finite elements of perfect knowledge or information, heavily bounded with assumptions and a range of applications. By doing so, these professions reduce the bounds and variability of uncertainty and thereby manage it. Using these hybrid models to acquire knowledge takes place in an economy (regulated or institutional) and environment (transparent and structured), which puts pressure on the various professions to recognize and use qualitative and quantitative knowledge better to reduce uncertainties in their activities. The challenges in this reflect the nature of the profession's or discipline's knowledge (e.g., scientific, engineering, or medical), the policies and structure of the relevant professional knowledge bodies, process objectives and constraints, and "the elusive demands of politics." [6] One common theme runs through all of these efforts to address the presence of uncertainty in professional activities. <br>
	:"The available scientific information upon which a decision must be made is almost always a mixture of engineering knowledge and uncertainty. Regardless of the information or methodology, there is the potential for error. This is true regardless of the relevant science, whether archaeology or aeronautics, economics or engineering, pharmacology or toxicology or epidemiology. Achieving the best social decisions requires not only understanding and using what we know but also appreciating and weighing the extent of our uncertainty. In making the best use of ... information in ... decision-making, it is still true that the beginning of wisdom is knowing what it is we do not know." (Vern, Op. cit., Reformatted and engineering substituted for scientific) <br>		:"The available scientific information upon which a decision must be made is almost always a mixture of engineering knowledge and uncertainty. Regardless of the information or methodology, there is the potential for error. This is true regardless of the relevant science, whether archaeology or aeronautics, economics or engineering, pharmacology or toxicology or epidemiology. Achieving the best social decisions requires not only understanding and using what we know but also appreciating and weighing the extent of our uncertainty. In making the best use of ... information in ... decision-making, it is still true that the beginning of wisdom is knowing what it is we do not know." (Vern, Op. cit., Reformatted and engineering substituted for scientific) <br>
	'''Driven by practical objectives and benefiting from past experience, knowledge professions such as engineering start by reasoning from uncertainty to develop explanations, calculate, and make predictions. This professional knowledge converges on but never reaches certainty, producing a "legitimacy" from the fruitfulness of its use.''' <ref>Randomness Is Unpredictability, Antony Eagle, The British Journal for the Philosophy of Science, Vol. 56, No. 4 (Dec., 2005), pp. 749-790 </ref> <br>
	[[#top\|Top of current page]]		[[#top\|Top of current page]]
	=== Bias and Uncertainty ===		=== Bias and Uncertainty ===
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	===Software Development Process- Risk Focused===		===Software Development Process- Risk Focused===
	The Unified Process requires the project team to focus on addressing the most critical risks early in the project life		The Unified Process requires the project team to focus on addressing the most critical risks early in the project life
	cycle. The deliverables of each iteration, especially in the Elaboration phase, must be selected to ensure that the greatest risks are addressed first. <ref> Booch, Grady, Ivar Jacobson, and James Rumbaugh. "The unified software development process."
	Reading: Addison Wesley (1999).</ref>		Reading: Addison Wesley (1999).</ref>
	===American Society of Civil Engineers (ASCE)===		===American Society of Civil Engineers (ASCE)===
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	...		...
	=== American Association of Cost Engineers (AACE) ===		=== American Association of Cost Engineers (AACE) ===
	AACE defined uncertainty, risk, and other related terms in its Risk Management Dictionary. <ref>Risk Management Committee uRisk Management Dictionary, Cost Engineering Vol. 37/No. 10, OCTOBER 1995. </ref>
	AACE's overall strategy was to define risk and other terms that stem from base uncertainty. AACE first defined uncertainty as .... "(t)he total range of events that may happen and produce risks (including both threats and opportunities) affecting a project (see opportunities, events, conditions, risk, and threats" where the following sub-definitions apply:		AACE's overall strategy was to define risk and other terms that stem from base uncertainty. AACE first defined uncertainty as .... "(t)he total range of events that may happen and produce risks (including both threats and opportunities) affecting a project (see opportunities, events, conditions, risk, and threats" where the following sub-definitions apply:
	** Biases--A lack of objectivity based on the individual's position or perspective. Systematic and predictable relationships between a person's opinion or statement and his/her underlying knowledge or circumstances. Note: there may be "system biases" as well as "individual biases."		** Biases--A lack of objectivity based on the individual's position or perspective. Systematic and predictable relationships between a person's opinion or statement and his/her underlying knowledge or circumstances. Note: there may be "system biases" as well as "individual biases."
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	</ol>		</ol>
	==References==		==References==
	~~<references />~~

	==References==		==References==

			==Notes==

			==References==
			'''Certainty''' has been defined as "an epistemic property" of knowledge in all its forms and the state of our beliefs about that knowledge. <ref name="Note3"/> Certainty about any belief about knowledge in any form implies that it is not subject to doubt or skepticism. This immunity to criticism can be dogmatically based, emphasizing the importance of a propositional-based sense of truth over experiential, sensory perceptions. <ref name="Note4"/>
			<ref name="Note3">Certainty defined as an epistemic property in ''Fox, D. (Year). Title of the Book. Publisher.''</ref>
			<ref name="Note4">The importance of propositional truth over experiential perception as discussed in ''Fox, D. (Year). Title of the Book. Publisher.''</ref>
			'''Uncertainty''', on the other hand, arises immediately in the slightest amount of doubt or criticism. <ref name="Note3">[Note 3]</ref> Similarly, a general definition of uncertainty could be given as "...any departure from the unachievable goal of complete determinism." <ref name="Reference5">[5]</ref> Reasoning under uncertainty is very different than performing the same under certainty. In reasoning under certainty, one has complete knowledge and deduces without doubt and equally important, without limitation, thereby concluding free from error. Reasoning under uncertainty, one works in a state of incomplete, inconsistent, and limited knowledge; doubts cloud any statements or assertions and thereby taint any deductions/inferences resulting in the potential for error. <ref name="Note4">[Note 4]</ref>
			<references>
			<ref name="Note3">[Note 3]</ref>
			<ref name="Reference5">[5]</ref>
			<ref name="Note4">[Note 4]</ref>
			'''Driven by practical objectives and benefiting from past experience, knowledge professions such as engineering start by reasoning from uncertainty to develop explanations, calculate, and make predictions. This professional knowledge converges on but never reaches certainty, producing a "legitimacy" from the fruitfulness of its use.''' <ref>Randomness Is Unpredictability, Antony Eagle, The British Journal for the Philosophy of Science, Vol. 56, No. 4 (Dec., 2005), pp. 749-790 </ref> <br>
			cycle. The deliverables of each iteration, especially in the Elaboration phase, must be selected to ensure that the greatest risks are addressed first. <ref> Booch, Grady, Ivar Jacobson, and James Rumbaugh. "The unified software development process."
			AACE defined uncertainty, risk, and other related terms in its Risk Management Dictionary. <ref>Risk Management Committee uRisk Management Dictionary, Cost Engineering Vol. 37/No. 10, OCTOBER 1995. </ref>
			<references />
	<ref name="Note3">[Note 3]</ref></ref>		<ref name="Note3">[Note 3]</ref></ref>
	<ref name="Note4">[Note 4]</ref></ref>		<ref name="Note4">[Note 4]</ref></ref>
	<ref name="Reference5">[5]</ref></ref>		<ref name="Reference5">[5]</ref></ref>
			<references />

WikiSysop: Created page with "'''Life is short and the art long; the occasion instant, experiment perilous, decision difficult.''' (Hippocrates as quoted in Fox,) See also Project Definition , Project Life Cycle and Phase Models , Project Delivery Methods
See also Technical Outcomes for Civil Engineering:Risk and Uncertainty ==Basic Considerations== As human beings,'' ... being alive means seeking opportunities and taking risks.'' As knowledge professionals living in the 21st ce..."

2024-11-23T16:43:32Z

Created page with "'''Life is short and the art long; the occasion instant, experiment perilous, decision difficult.''' (Hippocrates as quoted in Fox,) See also Project Definition , Project Life Cycle and Phase Models , Project Delivery Methods <br> See also Technical Outcomes for Civil Engineering:Risk and Uncertainty ==Basic Considerations== As human beings,'' ... being alive means seeking opportunities and taking risks.'' As knowledge professionals living in the 21st ce..."

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