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Leyla Acaroglu Paper beats plastic How to rethink environm.docx
- 1. Leyla Acaroglu: Paper beats plastic? How to rethink environmental folklore User: n/a - Added: 2/11/14 YouTube URL: http://www.youtube.com/watch?v=2L4B- Vpvx1A https://www.youtube.com/t/privacy_guidelines 1 ICS 5: Global Disruption and Information Technology 2 What is Sustainability?
- 2. “Sustainability is giving future generations as many opportunities as, if not more than, we have had ourselves” (Serageldin, 2006) “Meeting the needs of the present generation without compromising the ability of future generations to meet their needs.” (Brundtland, 1987) 3 Sustainability (NSF) “a sustainable world is one where human needs are met equitably without harm to the environment or sacrificing the ability of future generations to meet their own needs.” 4 Environmental Sustainability (Australian gov’t) Environmental sustainability is the ability to maintain the qualities that are valued in the physical environment. For example, most people want to sustain (maintain): • human life
- 3. • the capabilities that the natural environment has to maintain the living conditions for people and other species (eg. clean water and air, a suitable climate) • the aspects of the environment that produce renewable resources such as water, timber, fish, solar energy • the functioning of society, despite non-renewable resource depletion • the quality of life for all people, the livability and beauty of the environment 5 Environmental Sustainability (US President’s Council on Sustainable Development) America’s challenge is to create a life- sustaining Earth, a future in which prosperity and opportunity increase while life flourishes and pressures on the oceans, Earth and atmosphere diminish.
- 4. 6 Three legged stool 7 Nested model 8 Different stakeholders… Have different opinions. 9 The Value of a Definition Allows others to understand your argument, and determine whether or not they agree. Avoids miscommunication. Helps distill one’s thoughts.
- 5. 10 A Note on Definitions Not necessarily critical Mt. Everest Tenzing Norgay & Sir Edmund Hillary, 1953 11 Strategic Essentialism Working together despite differences. Different environmental groups, etc. 12 Global Climatic Disruption 13 What it’s called… Global warming
- 6. Global climate change Global weirding Global climatic disruption 14 15 Glo 16 Biodiversity Interactive Tree of Life • http://itol.embl.de/itol.cgi http://itol.embl.de/itol.cgi 17 18
- 7. 19 20 Biodiversity Where is most of the biodiversity? Where is most of the money interested in preserving biodiversity? 21 Biodiversity Breeds Robustness 22 Extinction Can’t recreate a species Can’t know all about what has been lost 23 The Sixth Extinction
- 8. by Leaky and Lewin (1995) Five major extinctions in the four billion year history of life. Dr. Richard Leakey, the world's most famous paleoanthropologist: Every year, between 17,000 and 100,000 species vanish from our planet, he says. "For the sake of argument, let's assume the number is 50,000 a year. Whatever way you look at it, we're destroying the Earth at a rate comparable with the impact of a giant asteroid slamming into the planet, or even a shower of vast heavenly bodies." Fifty per cent of the Earth's species will have vanished inside the next 100 years; mankind is using almost half the energy available to sustain life on the planet, and this figure will only grow as our population leaps from 5.7 billion to ten billion inside the next half-century. Such a dramatic and overwhelming mass extinction threatens the entire complex fabric of life on Earth, including the species
- 9. responsible for it: Homo sapiens. 24 25 Nevertheless… Certain species thrive: • Cows • Soybeans • Palms • Rats • Cockroaches • Dogs 26 Population >7 billion
- 10. 7,000,000,000 Scientific Notation • 7 x 10^9 • 7E+9 http://www.worldometers.info/ http://www.worldometers.info/ 27 28 IPAT Impact = Population x Affluence x Technology 29 Affluence Resources per person
- 11. 30 Impact of Technologies Enable both increase and decrease in both areas 31 Outcomes Live sustainably Undergo massive population reduction 32 Problem vs. Predicament Solution or no…
- 12. 33 ICS 5: Global Disruption and Information Technology Identifying Sustainable Designs Using Preferences over Sustainability Attributes Ganesh Ram Santhanam and Samik Basu and Vasant Honavar Department of Computer Science, Iowa State University, Ames, IA 50014 {gsanthan,sbasu,honavar}@iastate.edu Abstract We consider the problem of assessing the sustainability of alternative designs (e.g., for an urban environment) that are assembled from multiple components (e.g., water supply, transportation system, shopping centers, commercial spaces, parks). We model the sustainability of a design in terms of a set of sustainability attributes.
- 13. Given the (qualitative) preferences and tradeoffs of de- cision makers over the sustainability attributes, we for- mulate the problem of identifying sustainable designs as the problem of finding the most preferred designs with respect to those preferences. We show how techniques for representing and reasoning with qualitative prefer- ences can be used to identify the most preferred designs based on the decision maker’s stated preferences and tradeoffs. Introduction In many applications like urban planning, the design of green buildings and space crafts, decision makers often look for designs that are more sustainable than others among all the designs that satisfy the functional requirements. Typ- ically, the sustainability of the various alternative designs are assessed with respect to a set of sustainability attributes that describe various aspects of the designs such as its ini- tial and maintenance cost, the amount of pollutants (e.g., toxic, greenhouse gases) it releases into the environment, and the amount of renewable energy used to source the en- ergy needs of the design. Identifying the most sustainable designs among a set of alternatives depends on the prefer- ences and tradeoffs of the decision maker over such sustain-
- 14. ability attributes, in addition to the functional requirements of the design problem. For example, in designing a sustainable building, a deci- sion maker might prefer to source the energy needs of the building using renewable energy sources (such as solar or wind energy) over non-renewable energy sources (such as fossil fuels). Furthermore, the decision maker may choose to trade off one sustainability attribute against another (e.g., re- newability of the energy source against cost of the building); and in other settings, the decision maker might find it use- ful to assign relative importance to sustainability attributes Copyright c© 2011, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. (e.g., controlling the amount of greenhouse gas emissions being more important than using renewable energy sources). A similar problem arises in the design of space crafts (Lutz et al. 2010). In order to make a space craft design more sus- tainable for a mission, the decision maker may seek a more energy efficient space craft design, i.e., one which consumes lesser electricity per unit time in comparison to various other feasible designs of the space craft. This requires more en-
- 15. ergy efficient components (with lesser power ratings) to be used in the design of the space craft. Similarly, the decision maker may also want to minimize the cost of the initial de- sign of the space craft, and hence among two components with the same power ratings, the less expensive one may be part of the preferred design. In addition, the decision makers may also consider the overall cost of the design to be more important than its efficiency in terms of power consumption. Preferences such as the above may be qualitative (Brafman, Domshlak, and Shimony 2006) (e.g., binary preference re- lations over the domains) or quantitative (Fishburn 1970; Keeney and Raiffa 1993) (e.g., utility functions). Problems in sustainable design (e.g., building design) typ- ically involve choosing and assembling multiple compo- nents (such as siding walls, flooring and heating system in the case of a building design) from a repository that sat- isfy the functional requirements of the design. Each com- ponent of the design contributes to the sustainability of the design with respect to each of the sustainability attributes, and choosing some components over others to be included in the design might make the design more sustainable based on the preferences and tradeoffs of the decision maker over the sustainability attributes. The sustainability of a design is thus a function of the sustainability of the components that
- 16. make up the design and the decision maker’s stated prefer- ences and tradeoffs. In the sustainable design of a space craft (Lutz et al. 2010) for example, an expensive component simply adds to the cost of the entire space craft as a whole. However, the power rating of a space craft may not be a simple sum of the power ratings of its components. In fact it may depend on the ar- rangement of the components in parallel or sequence in the circuitry. Furthermore, in order to determine the subset of most sustainable designs among all feasible designs, there is a need to compare two designs with respect to all the sustain- ability attributes in terms of the intra-attribute and relative 91 Artificial Intelligence and Sustainable Design — Papers from the AAAI 2011 Spring Symposium (SS-11-02) https://www.researchgate.net/publication/223940146_SSB_Utili ty_Theory_and_Decision- Making_Under_Uncertainty?el=1_x_8&enrichId=rgreq- e8becdcc0d009a9e32cdfc191cd5c0e0- XXX&enrichSource=Y292ZXJQYWdlOzIyMTI1MDcyMTtBUz oyODc3NDA5OTk1NTMwMjRAMTQ0NTYxNDIwODY4OA==
- 19. 00&enrichId=rgreq-e8becdcc0d009a9e32cdfc191cd5c0e0- XXX&enrichSource=Y292ZXJQYWdlOzIyMTI1MDcyMTtBUz oyODc3NDA5OTk1NTMwMjRAMTQ0NTYxNDIwODY4OA== importance preferences of the stakeholders. This is called dominance testing, i.e., does one design dominate the other with respect to the stated sustainability preferences? Hence, in order to identify sustainable designs from a set of alternatives, there is a need for principled methods that assess and compare alternative designs based on (a) the pref- erences and tradeoffs of the decision maker with respect to the sustainability attributes, and (b) the impact of various components and materials that are included in the design. Our approach to the problem of identifying the most sus- tainable design(s) involves representing sustainability re- quirements (in addition to the functional requirements) of the decision makers in terms of qualitative preferences over a set of application specific sustainability attributes of the design alternatives. We propose to leverage the existing body of work in the AI literature for representing and reasoning with qualitative preferences over multiple attributes. Follow- ing the representation language given in (Santhanam, Basu,
- 20. and Honavar 2010b), we represent sustainability preferences of the decision makers in the form of: (a) intra-attribute pref- erences, i.e., preferences over the various possible values that can be taken by each attribute; and (b) relative impor- tance among the attributes, i.e., which of the sustainabil- ity attributes the stakeholders care more about. While intra- attribute preferences make one design preferred over another in terms of a particular attribute, relative importance prefer- ences allow one attribute to be traded off against others. In this paper we restrict our scope to preferences over an attributes that do not depend on specific values assigned to other attributes (i.e., unconditional preferences). However, our approach can be extended to use other more expressive languages, particularly CP-nets (Boutilier et al. 2004), TCP- nets (Brafman, Domshlak, and Shimony 2006), and UCP- nets (Boutilier, Bacchus, and Brafman 2001) that can rep- resent and reason with conditional preferences. We leverage on existing dominance testing strategies that are well studied in the AI literature (Santhanam, Basu, and Honavar 2010b; 2010a; Boutilier et al. 2004; Brafman, Domshlak, and Shi- mony 2006) that have been successfully used in other design applications such as Web services composition (Santhanam, Basu, and Honavar 2008). We provide a generic model and a practical approach that can be used along with existing
- 21. design tools for identifying sustainable designs in various application domains. Illustrative Example In order to explain our approach to sustainable design, we consider the problem of building design, where the deci- sion maker is tasked with identifying sustainable building designs from a set of candidate designs that meet some pre- specified functional requirements of the building. Sustainability attributes The sustainability of a building depends on how cost-effective, environmentally preferable and safe are the components and materials used in the de- sign. Key factors in determining the sustainability of a com- ponent used in the design of a building include its energy costs, potential global warming effects in terms of green- house gas emissions, and environmental, health, and safety concerns related to the potential release of toxic chemicals and pollutants from the components and materials (Lippiatt 2007). The Building for Environmental and Economic Sustain- ability (BEES 4.0) tool (Lippiatt 2007) released by the Na-
- 22. tional Institute of Standards and Technology (NIST1) con- siders several attributes for measuring sustainability of com- ponents and materials used in building design. This decision support tool is intended towards aiding building decision makers to choose components and materials in their design that increase the sustainability of the building as a whole. The tool includes actual environmental and economic per- formance data for 230 building products over these sustain- ability attributes. In our example we consider the following four attributes (included in the BEES tool) as indicators of sustainability of components for the purpose of this discus- sion. • Initial Cost (IC): This determines the cost of constructing the building as per the design. • Future Cost (FC): This determines the cost of maintaining and operating the building for its intended purpose. • Renewability (RE): This measures how much renewable (and non-renewable) energy is embodied in the materials used to construct the building. For example, the use of components that are made of renewable materials (such as wood) for components such as doors, windows, siding walls, etc. in the construction of the building, and the use
- 23. of renewable energy sources (such as solar power) to meet the energy needs of the building makes a design more sus- tainable in terms of this attribute. • Toxicity/Greenhouse Gas Emission (TG): During the con- struction and operation of a building, several chemicals are released into the environment. Ecological toxicity refers to the potential of a pollutant that is released into the environment to harm ecosystems. Similarly, green- house gases such as carbon dioxide (CO2) are believed to contribute to global warming, so a sustainable building will minimize the emissions of greenhouse gases during construction and operation. Preferences For each of the above attributes, we allow the following values: Excellent (E), Good (G), Average (A), Bad (B) and Poor (P). These levels indicate the sustainability of the component2, and the intra-attribute preferences for all the attributes correspond to E > G > A > B > P. For exam- ple, a component that has ‘P’ as the value of the attribute Re- newability (RE), it indicates that the component consumes a lot of non-renewable energy sources, and is not preferable to another component valued at ‘B’ for RE. Similarly, a com- ponent that has ‘A’ for the attribute initial cost (IC) is con-
- 24. 1http://www.nist.gov 2The BEES 4.0 (Lippiatt 2007) tool provides values on a nu- meric scale for each of the attributes for the components, but we use qualitative levels that roughly correspond to those numerical values in order to simplify our discussion in our paper. 92 https://www.researchgate.net/publication/242489366_Building_ for_Environmental_and_Economic_Sustainability_Technical_M anual_and_User_Guide?el=1_x_8&enrichId=rgreq- e8becdcc0d009a9e32cdfc191cd5c0e0- XXX&enrichSource=Y292ZXJQYWdlOzIyMTI1MDcyMTtBUz oyODc3NDA5OTk1NTMwMjRAMTQ0NTYxNDIwODY4OA== https://www.researchgate.net/publication/242489366_Building_ for_Environmental_and_Economic_Sustainability_Technical_M anual_and_User_Guide?el=1_x_8&enrichId=rgreq- e8becdcc0d009a9e32cdfc191cd5c0e0- XXX&enrichSource=Y292ZXJQYWdlOzIyMTI1MDcyMTtBUz oyODc3NDA5OTk1NTMwMjRAMTQ0NTYxNDIwODY4OA== https://www.researchgate.net/publication/242489366_Building_ for_Environmental_and_Economic_Sustainability_Technical_M anual_and_User_Guide?el=1_x_8&enrichId=rgreq-
- 26. https://www.researchgate.net/publication/220543098_CP- nets_A_Tool_for_Representing_and_Reasoning_with_Condition al_Ceteris_Paribus_Preference_Statements?el=1_x_8&enrichId= rgreq-e8becdcc0d009a9e32cdfc191cd5c0e0- XXX&enrichSource=Y292ZXJQYWdlOzIyMTI1MDcyMTtBUz oyODc3NDA5OTk1NTMwMjRAMTQ0NTYxNDIwODY4OA== https://www.researchgate.net/publication/220543049_On_Graph ical_Modeling_of_Preference_and_Importance?el=1_x_8&enric hId=rgreq-e8becdcc0d009a9e32cdfc191cd5c0e0- XXX&enrichSource=Y292ZXJQYWdlOzIyMTI1MDcyMTtBUz oyODc3NDA5OTk1NTMwMjRAMTQ0NTYxNDIwODY4OA== https://www.researchgate.net/publication/220543049_On_Graph ical_Modeling_of_Preference_and_Importance?el=1_x_8&enric hId=rgreq-e8becdcc0d009a9e32cdfc191cd5c0e0- XXX&enrichSource=Y292ZXJQYWdlOzIyMTI1MDcyMTtBUz oyODc3NDA5OTk1NTMwMjRAMTQ0NTYxNDIwODY4OA== Function Component IC FC RE TG Heating Electric G B B B Heating Gas A G B B Heating Solar P E E E Flooring Ceramic Tile A E B B Flooring Vinyl Tile E G A G
- 27. Flooring Natural Cork P E G E Siding Brick&Mortar P E P B Siding Aluminum G G G A Siding Cedar A A G G Table 1: Available Building Components in the Repository Design Heating Flooring Siding D1 Electric Vinyl Tile Aluminum D2 Gas Ceramic Tile Brick&Mortar D3 Gas Vinyl Tile Aluminum D4 Solar Ceramic Tile Brick&Mortar D5 Solar Natural Cork Aluminum Table 2: Candidate Building Designs sidered more economically sustainable (less expensive) than another with a level of ‘P’. Furthermore, suppose that the the decision maker has some preferences in terms of the relative importance of the sustainability attributes, such that: • Future Cost is more important than Initial Cost and Re-
- 28. newability • Toxicity/Greenhouse gas emission is more important than Initial Cost Functional Requirements In order to simplify the discus- sion, we consider only three aspects of the functional re- quirements of a building design: (a) the heating mechanism; (b) the type of flooring; and (c) the type of external wall sid- ing used in the design. Suppose that the only choices avail- able (for each of the components in the repository) are as given in Table 1. The table also shows the valuations3 of the components with respect to the sustainability attributes. A candidate design constitutes a combination of the heat- ing mechanism (Electric/Gas/Solar), type of flooring (Ce- ramic Tile/Vinyl Tile/Natural Cork), and external wall sid- ing (Brick&Mortar/Aluminum/Cedar), thus satisfying the functional requirements. Suppose that the decision maker is tasked with choosing the most sustainable design(s) from five candidate building designs as given in Table 2. In this example, the problem we address corresponds to identifying the most sustainable design(s) from those given in Table 2, i.e., designs with preferred values (closer to E)
- 29. 3The valuations for the flooring and external siding wall com- ponents are roughly based on data for the respective materials from the BEES 4.0 (Lippiatt 2007) tool. for the sustainability attributes, while at the same time re- specting the relative importance among the attributes. Model Designs and Feasible Designs A design problem consists of a repository of available com- ponents from which we are interested in assembling designs that satisfy some given functionality ϕ. Formally, we repre- sent a design problem as a tuple 〈R, ⊕, |=, ϕ〉 where • R = {C1, C2 . . . Cr} is a set of available components • ⊕ denotes a design operator that functionally aggregates components and encodes how the components interact when included within the same design. ⊕ is a binary op- eration on components Ci, Cj in the repository that pro- duces a design Ci ⊕ Cj
- 30. • |= is a satisfaction relation that evaluates to true when a design satisfies the given functional requirements ϕ • ϕ is a set of functional requirements that each candidate solution to the design problem is required to satisfy Definition 1 (Candidate or Feasible Design). Given a design problem 〈R, ⊕, |=, ϕ〉, a design D = Ci1 ⊕ Ci2 ⊕ . . . Cin is an arbitrary collection of components Ci1, Ci2, . . . , Cin s.t. ∀ j ∈ [1, n] : Cij ∈ R. A feasible design or a candidate design is a design D that satisfies the functional requirements ϕ, denoted by D |= ϕ. The repository of available components R in our example problem of building design is given in Table 1. The func- tional requirements ϕ in our problem state that a building design is feasible if it includes exactly one heating compo- nent (electric, gas, or solar heating), one flooring component (ceramic, vinyl tile, or natural cork) and one siding compo- nent (brick&mortar, aluminum or cedar siding). The set of candidate or feasible designs considered in the example is given Table 2. Sustainability Attributes
- 31. Let X = {X1, X2, ..Xn} be the set of sustainability at- tributes in a design problem, each Xi having a domain of possible values Domi. We define the valuation of a compo- nent in terms of the sustainability attributes as follows, simi- lar to the definition of the valuation of Web services with re- spect to their non-functional properties in (Santhanam, Basu, and Honavar 2008). Definition 2 (Valuation of a Design Component). The val- uation of a component Cj ∈ R with respect to the at- tribute Xi ∈ X is denoted by VCj (Xi). The overall valu- ation of the component Cj is described by the tuple VCj = 〈VCj (X1), VCj (X2), . . . VCj (Xn)〉 of valuations. In our running example, the sustainability attributes are X = {IC, FC, RE, TG}, and all the attributes have the same domain, namely {E, G, A, B, P}. According to the above definition, the overall val- uation of the heating component Gas with re- spect to the above sustainability attributes is: VGas = 〈VGas(IC), VGas(FC), VGas(RE), VGas(TG)〉 = 〈G, B, B, B〉. 93
- 32. Preferences over Sustainability Attributes Our goal is to find the most preferred designs among those that are feasible, with respect to a set of sustainability at- tributes X. In order to identify the most preferred designs, it is necessary that the decision maker specifies his/her pref- erences over the attributes. We propose to represent prefer- ences over the values of the sustainability attributes X as follows. • Intra-attribute preferences (�i): For each attribute Xi, �i is a binary preference relation on Domi such that if u, v ∈ Domi then u �i v if and only if u is preferred to v in terms of the sustainability attribute Xi. • Relative importance preferences (�): Given a set of sus- tainability attributes X, � is a binary preference relation on X such that Xi � Xj if and only if Xi is relatively more important than Xj . In our example of building design, the intra-attribute pref- erences can be represented as E �i G �i A �i B �i P , i = {IC, FC, RE, TG} and the relative importance pref-
- 33. erences can be represented as FC � IC, FC � RE and TG � IC.