A White Paper on Locational Information and the Public Interest

Abstract

The first goal of the Summit was to identify a research agenda on locational information and the public interest, outlining research questions that cut across disciplines, examining the ethical issues that could be addressed to improve the current challenges in spatial analytics, and identifying knowledge gaps that were not yet researched. Many issues could be raised, for example bias and harm to racialized communities. Since not all could be covered, seven groups of agenda items were identified, including (1) Privacy and Anonymization, (2) Data Technology and Its Social-Psychological Dimension, (3) Utility, (4) Technical Approaches to Privacy Protection, (5) Data Infrastructure: Virtual Data Enclaves and Processes, (6) Co-Design and Inclusivity, and (7) Ethical Implications of the User Experience.

Crossing Boundaries: The Ethics of AI and Geographic Information Technologies

“…Benchmark & EthicalGeo [64] note that "the number, variety and accessibility of digital mapping has created risks and opportunities that are new in kind and scale", and so users "should have help to understand potential harms from their activity". Similarly, Goodchild et al [65] state that we have now reached a point "where a largely unregulated mix of government, nonprofit, and corporate agencies have access" to geo-information on a large proportion of the world, which may be beneficial, but "too often they are or can become intrusive or serve oppressive purposes". Echoing this sentiment, the Ordnance Survey [67] states that controls and frameworks may need to be drawn up to supervise data collection and use.…”

“…As Benchmark & EthicalGeo [64] clearly states, users of location data have the responsibility "to understand the potential effects of their uses of data, including knowing who (individuals and groups) and what could be affected, and how". Goodchild et al [65] extend the target of where responsibility lies, stating that the "regulatory parameters for geospatial data collection and use must be applicable to all aspects of supply-chain management, including companies that contract to provide products and services to multinational corporations". Likewise, the Geospatial Commission [66] asserts that those "working with location data (across all sectors of the UK economy and the public sector) share responsibility for the public's trust in the location data ecosystem".…”

Symbolic and subsymbolicGeoAI: Geospatial knowledge graphs and spatially explicit machine learning

“…(3) Given the increasing popularity of foundation models (FMs) in the natural language and vision communities, such as GPT-3 (Brown et al, 2020), CLIP (Radford et al, 2021), PaLM (Wei et al, 2022), and DALL•E2 (Ramesh et al, 2022), could we build a FM for GeoAI which, after pretraining, can be easily adapted to multiple symbolic GeoAI and subsymbolic GeoAI tasks, involving the use of different data modalities (Mai et al, 2022a)? (4) How can we address important ethical aspects, such as better accounting for and mitigating issues of bias, fairness, and transparency (Shin & Basiri, 2022;Zheng & Sieber, 2022), how to reduce the environmental footprint of model training, and how to better connect to communities studying ethics of technology (Goodchild et al, 2022).…”

A Usable Encryption Solution for File-Based Geospatial Data within a Database File System

“…GIS data are a key component of decision-making in high-risk scenarios such as humanitarian and natural disasters. Timely access to relevant spatial data is of the utmost importance under these conditions; however, it is also important to understand that although there is a great need for data to be highly available, keeping this data secure is critical, as recently highlighted by researchers [1][2][3][4][5][6]. Almost 60-80% of all generated data have some geographic component to them [7], and, adding to this, the complexities associated with spatial data have increased dramatically [8].…”