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Looking at the Future of Multifactor Authentication
Biometrics are just one means of multifactor authentication–but what does the future of authentication look like?
multifactor-authentication  three-factor-authentication  biometrics  artificial-intelligence 
yesterday by Adventure_Web
[1709.08071] Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems
Much research in artificial intelligence is concerned with the development of autonomous agents that can interact effectively with other agents. An important aspect of such agents is the ability to reason about the behaviours of other agents, by constructing models which make predictions about various properties of interest (such as actions, goals, beliefs) of the modelled agents. A variety of modelling approaches now exist which vary widely in their methodology and underlying assumptions, catering to the needs of the different sub-communities within which they were developed and reflecting the different practical uses for which they are intended. The purpose of the present article is to provide a comprehensive survey of the salient modelling methods which can be found in the literature. The article concludes with a discussion of open problems which may form the basis for fruitful future research.
agent-based  collective-behavior  machine-learning  artificial-intelligence  open-problems  nudge-targets  to-write-about 
7 days ago by Vaguery
[1709.04524] Workflow Complexity for Collaborative Interactions: Where are the Metrics? -- A Challenge
In this paper, we introduce the problem of denoting and deriving the complexity of workflows (plans, schedules) in collaborative, planner-assisted settings where humans and agents are trying to jointly solve a task. The interactions -- and hence the workflows that connect the human and the agents -- may differ according to the domain and the kind of agents. We adapt insights from prior work in human-agent teaming and workflow analysis to suggest metrics for workflow complexity. The main motivation behind this work is to highlight metrics for human comprehensibility of plans and schedules. The planning community has seen its fair share of work on the synthesis of plans that take diversity into account -- what value do such plans hold if their generation is not guided at least in part by metrics that reflect the ease of engaging with and using those plans?
computational-complexity  performance-measure  to-understand  what-gets-measured-gets-fudged  nudge  to-write-about  engineering-design  philosophy-of-engineering  machine-learning  artificial-intelligence 
13 days ago by Vaguery
Social Choice Ethics in Artificial Intelligence by Seth D. Baum :: SSRN
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A major approach to the ethics of artificial intelligence (AI) is to use social choice, in which the AI is designed to act according to the aggregate views of society. This is found in the AI ethics of “coherent extrapolated volition” and “bottom-up ethics”. This paper shows that the normative basis of AI social choice ethics is weak due to the fact that there is no one single aggregate ethical view of society. Instead, the design of social choice AI faces three sets of decisions: standing, concerning whose ethics views are included; measurement, concerning how their views are identified; and aggregation, concerning how individual views are combined to a single view that will guide AI behavior. These decisions must be made up front in the initial AI design — designers cannot “let the AI figure it out”. Each set of decisions poses difficult ethical dilemmas with major consequences for AI behavior, with some decision options yielding pathological or even catastrophic results. Furthermore, non-social choice ethics face similar issues, such as whether to count future generations or the AI itself. These issues can be more important than the question of whether or not to use social choice ethics. Attention should focus on these issues, not on social choice.
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Uh, duh, but it's nice to have someone parse this out.
artificial-intelligence  ethics  philosophy  papers 
14 days ago by absfac
Building smarter cars with smarter factories: How AI will change the auto business - McKinsey & Company
From driverless cars to robots on the factory floor, AI is transforming the automotive industry. Here are the steps smart companies are taking to seize the opportunities it offers.
artificial-intelligence  automation  internet-of-things  autonomous-vehicles  automotive-industry  shop-floor  industry4.0  Around-the-web  this-week-398 
15 days ago by areadevelopment

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