MORPH: A Reference Architecture for Configuration and Behaviour Self-Adaptation

An architectural approach to self-adaptive systems involves runtime change of system configuration (i.e., the system's components, their bindings and operational parameters) and behaviour update (i.e., component orchestration). Thus, dynamic reconfiguration and discrete event control theory are at the heart of architectural adaptation. Although controlling configuration and behaviour at runtime has been discussed and applied to architectural adaptation, architectures for self-adaptive systems often compound these two aspects reducing the potential for adaptability. In this paper we propose a reference architecture that allows for coordinated yet transparent and independent adaptation of system configuration and behaviour

Fragmentation and the Future: Investigating Architectures for International AI Governance

The international governance of artificial intelligence (AI) is at a crossroads: should it remain fragmented or be centralised? We draw on the history of environment, trade, and security regimes to identify advantages and disadvantages in centralising AI governance. Some considerations, such as efficiency and political power, speak for centralisation. The risk of creating a slow and brittle institution, and the difficulty of pairing deep rules with adequate participation, speak against it. Other considerations depend on the specific design. A centralised body may be able to deter forum shopping and ensure policy coordination. However, forum shopping can be beneficial, and fragmented institutions could self-organise. In sum, these trade-offs should inform development of the AI governance architecture, which is only now emerging. We apply the trade-offs to the case of the potential development of high-level machine intelligence. We conclude with two recommendations. First, the outcome will depend on the exact design of a central institution. A well-designed centralised regime covering a set of coherent issues could be beneficial. But locking-in an inadequate structure may pose a fate worse than fragmentation. Second, fragmentation will likely persist for now. The developing landscape should be monitored to see if it is self-organising or simply inadequate.One of the authors, Luke Kemp, was generally funded through the support of a grant from the Templeton World Charity Foundation, Inc

A framework for monitoring and assisting seniors with memory disabilities

Population aging brings increased social problems. Solutions for this new reality must be devised. Providing care services at home may benefit patients, health service providers, and social security systems and needs to be seen as a possible solution for those social problems. By maintaining the patient at home, in his or her own environment, care services costs can be diminished and, at the same time, the comfort and well-being of the person in need are significantly increased. To pursue this goal, we explore the advantagesThe work of Davide Carneiro is supported by a doctoral grant by the Fundação para a Ciência e a Tecnologia (FCT, Portuguese Foundation for Science and Technology; SFRH/ BD/64890/2009). The work of Angelo Costa is supported by a research grant by the FCT within the project PTDC/JUR/71354/2006 and PEst-OE/EEI/UI0752/201

The deception of an infinite view – exploring machine vision in digital art

This paper examines prediction product called Queryable Earth a project to “make Earth searchable for all”. A project pitched by the company Planet, owner of the largest fleet of Earth-imaging satellites in orbit and an archive of satellite images growing with terabytes of fresh data every day. The aim of Queryable Earth is to combine geospatial intelligence with machine learning. By training artificial neural networks to classify objects, identify geographic features, and monitor change over time, the implied intention is to create a predictive, omniscient oracle. In this paper Queryable Earth functions as an example of a ‘nonconscious cognitive assemblage’ combining aerial image with machine learning techniques such as artificial neural networks. To examine the predictive potential and the assumed objectivity of machine vision systems such as Queryable Earth I turn to histories of aerial photography and examples of contemporary digital art to illustrate how human and technical cognition entwine revealing how seemingly automated processes such as rendering of satellite images and pattern recognition still inherit human biases and are prone to emphasize them. Furthermore, I use digital artworks to illustrate how Queryable Earth as an “all seeing machine” is limited to a singular aerial perspective which cannot penetrate the surface and how predictions produced by such systems are constrained the quality and selection of data they are trained on