互联网金融风险与政府治理机制转型

目的/意义人工智能的飞速发展,一方面为政府治理提供了新的途径,但同时也带来了极大的挑战。因此,在人工智能背景下,如何优化政府智能决策模型、提高政府决策的效率和科学性就显得尤为重要。设计/方法从政府治理中智能决策的相关理论入手,对影响政府智能决策的内部因素和外部因素展开了研究,探讨了融合多源信息进行政府智能决策的问题。结论/发现构建了基于政府内外部信息的多源信息融合模型和政府智能决策系统,为智能化政务办公的发展提供强有力支撑。     

Sufficient reduction methods for multivariate time-dependent health surveillance data

ABSTRACT

Early detection with a low false alarm rate (FAR) is the main aim of outbreak detection as used in public health surveillance or in regard to bioterrorism. Multivariate surveillance is preferable to univariate surveillance since correlation between series (CBS) is recognized and incorporated. Sufficient reduction has proved a promising method for handling CBS, but has not previously been used when correlation within series (CWS) is present. Here we develop sufficient reduction methods for reducing a p-dimensional multivariate series to a univariate series of statistics shown to be sufficient to monitor a sudden, but persistent, shift in the multivariate series mean. Correlation both within and between series is taken into account, as public health data typically exhibit both forms of association. Simultaneous and lagged changes and different shift sizes are investigated. A one-sided exponentially weighted moving average chart is used as a tool for detection of a change. The performance of the proposed method is compared with existing sufficient reduction methods, the parallel univariate method and both VarR and Z charts. A simulation study using bivariate normal autoregressive data shows that the new method gives shorter delays and a lower FAR than other methods, which have high FARs when CWS is clearly present.     

Surveillance of the interaction parameter of the ising model

Surveillance to detect changes of spatial patterns is of interest in many areas such as environmental control and regional analysis. Here the interaction parameter of the Ising model, is considered. A minimal sufficient statistic and its asymptotic distribution are used. It is demonstrated that the convergence to normal, distribution is rapid. The main result is that when the lattice is large, all approximations are better in several respects. It is shown that, for large lattice sizes, earlier results on surveillance of a normally distributed random variable can be used in cases of most interest. The expected delay of alarm at a fixed level of false alarm probability is examined for some examples.     

Hard and Soft Commitments to Human Rights Treaties, 1966–20001

What factors determine whether and how deeply countries will commit to the international human rights regime? Using data for up to 142 countries between 1966 and 2000, this article analyzes patterns of membership to the International Human Rights Covenants. The analysis produced two main conclusions. First, the potential costs associated with joining a treaty, rather than its substantive content, motivates the decision to join. Treaties that protect different rights but establish comparable implementation mechanisms exhibit similar patterns of membership, whereas treaties that protect identical rights but establish different implementation provisions exhibit dissimilar patterns of membership. Second, rates of treaty membership differ by level of commitment. Countries that sign human rights treaties differ from countries that ratify. Results are interpreted with respect to four theories of commitment and compliance: realism, liberalism, constructivism, and sociological institutionalism. Theories that emphasize the importance of a treaty’s costs (realism and institutionalism) fare better than theories that prioritize a treaty’s content (liberalism and constructivism).     

Undercover policing and the spectre of ‘domestic extremism’: the covert surveillance of environmental activism in Britain

The spectre of environmental ‘domestic extremism’ has long been postulated by police leaders and security analysts in Britain. It is a narrative that has justified the commitment of enormous amounts of government resources towards police intelligence work directed at non-violent direct action campaigns. Most controversially, this has included the long-term infiltration of environmental (and other) activist groups by undercover police. This article provides a critical analysis of the justifications put forward in support of the covert surveillance of environmental activists in Britain. The paper proceeds by way of a single case study – a high profile, environmental direct action protest in the north of England – in order to reveal the levels of abuse, manipulation and deception at the basis of undercover protest policing. Through their court case, the activists involved with this action were able to obtain rare insights into the police authorisation documents for the undercover operation that had led to their arrests. An analysis of these documents provides us with a glimpse of the contradictory justifications given by senior police officers for infiltration – now under scrutiny by a public inquiry.     

Machine Learning for Drug Overdose Surveillance

ABSTRACT

We describe two recently proposed machine learning approaches for discovering emerging trends in fatal accidental drug overdoses. The Gaussian Process Subset Scan (Herlands, McFowland, Wilson, & Neill, 2017 Neill, D. B. (2017). Multidimensional tensor scan for drug overdose surveillance. Journal of Public Health Informatics, 9(1), e20. doi:10.5210/ojphi.v9i1.7598[Crossref] , [Google Scholar]) enables early detection of emerging patterns in spatio-temporal data, accounting for both the complex, correlated nature of the data and the fact that detecting subtle patterns requires integration of information across multiple spatial areas and multiple time steps. We apply this approach to 17 years of county-aggregated data for monthly opioid overdose deaths in the New York City metropolitan area, showing clear advantages in the utility of discovered patterns as compared to typical anomaly detection approaches. To detect and characterize emerging overdose patterns that differentially affect a subpopulation of the data, including geographic, demographic, and behavioral patterns (e.g., which combinations of drugs are involved), we apply the Multidimensional Tensor Scan (Neill, 2017 Neill, D. B. (2017). Multidimensional tensor scan for drug overdose surveillance. Journal of Public Health Informatics, 9(1), e20. doi:10.5210/ojphi.v9i1.7598[Crossref] , [Google Scholar]) to 8 years of case-level overdose data from Allegheny County, Pennsylvania. We discover previously unidentified overdose patterns which reveal unusual demographic clusters, show impacts of drug legislation, and demonstrate potential for early detection and targeted intervention. These approaches to early detection of overdose patterns can inform prevention and response efforts, as well as understanding the effects of policy changes.     

Blood,Sweat, and Tears: Navigating Creepy versus Cool in Wearable Biotech

ABSTRACT

This paper considers how personal data protections figure into the design process of wearable technology. The data question is becoming especially important in the face of recent innovations in biotechnology that capitalize on the new fungibility of biology and electronics, in which new biotech wearables capitalize on the ability to analyze and track changes in blood, sweat, and tears. Interviews and participant observation with wearable tech designers, data scientists, fashion tech entrepreneurs, and select experts in cybersecurity and intellectual property law, reveal a range of approaches to data protection in design within the culture where wearables are beginning to merge with biotech. While a few respondents were extremely vigilant about protecting consumer’s privacy, the majority felt that when consumers ‘opt in’ to data sharing, they should be cognizant of the risks. From their perspective, it is not necessarily the producer’s responsibility to protect user's personal data. These attitudes present a problematic logic, which leaves users vulnerable to data exploitation. The paper concludes by arguing that this laissez-faire culture is the environment in which wearable biotech is being developed and will be deployed. This emerging technology raises issues about bodies, data, and ownership in crucial need of analysis and critique to push its move into the mainstream toward more equitable and inclusive ends.     

The privacy paradox: how market privacy facilitates government surveillance

Although most surveillance studies scholars assume privacy is antithetical to surveillance, critics have recently warned that privacy-based criticisms may facilitate surveillance. That being said, we do not yet have data that show whether privacy claims were used in the past to legitimate government surveillance. This paper addresses that gap by analyzing claims made over one of the U.S.’s most controversial surveillance issues: government control over encryption technologies. A review of Congressional hearings and statements on the Congressional Record (n?=?112) reveals that from 1993 to 1999, public debates were dominated by a market liberalization discourse in which participants supported loosening encryption controls as a way to protect privacy from criminal intrusions in market transactions. Also playing a role was a strong skepticism toward government power and a preference for markets as managers of crime prevention. Challenged by these critiques, lawmakers withdrew regulatory proposals and spent the following decade working quietly with private firms to ensure law enforcement surveillance capability. These findings show the expansion of privacy for consumers and entrepreneurs has in fact been used to achieve the contraction of privacy from law enforcement and intelligence agencies.     

Mass-mediated surveillance: borders,mobility, and reality television

This article analyzes the social construction of border surveillance and policing in reality-based television. Utilizing content analytic methods to document and decode popular images of borders, mobility, and insecurity, it assesses three programs from Australia, the UK, and the United States. Despite claims of offering accurate and unfiltered depictions, the programs are ideological and provide visions of enforcement that reinforce stereotypes regarding the risks of permeable borders and exonerate intensive regimes of surveillance and securitization. Our findings suggest this occurs in three ways. First, the programs inflate the extent and seriousness of lawlessness associated with cross-border movement. Second, they offer individualistic explanations of crime that cite personal choices and pathologies as determinants. Finally, alongside neglecting their perspectives and interpretations of events, when compared to the reality of official statistics, the programs disproportionately feature suspected offenders as members of marginalized groups. The social and political implications of these findings are discussed.     

Rating the revolution: Silicon Valley in normative perspective

Silicon Valley, California – home of Apple, Facebook, Twitter, Google, and so on – is widely regarded as the epicentre of the information revolution. However, it is not just a technical or economic phenomenon; it has also made a social revolution. The article evaluates Silicon Valley from a normative perspective, seeking to identify its real societal impact, negative as well as positive. A select review of significant literature is followed by exposition of primary data, based on in situ face-to-face interviews with Valley occupants; these range from the chief technology officer of a global brand to a homeless, unemployed Vietnam War veteran. The article organises its findings under three headings: the nature of information revolution; iCapitalism as a new technoeconomic synthesis; and the normative crisis of the information society. It concludes with a warning about ongoing attempts to clone Silicon Valley around the world.