About

About the Chair

The Future of Heritage Crime is not what we Expect

Rapid advances in technology and the complexity of global markets have created new opportunities for heritage crime. We face significant challenges in adequately safeguarding global heritage against emerging crimes that occur at and beyond the boundaries of detection, deterrence, and imagination.

The UNESCO Chair in Cultural Heritage and Emerging Crime, held by criminologist Donna Yates, responds to these challenges by exploring emerging heritage crimes related to contemporary crises whose causes may be known but whose implications are not. Inherently forward-facing, the Chair seeks to develop academic and practical pathways for understanding heritage crime that may arise in the near or distant future, but that we have no existing capacity to predict, detect, or prevent. The Chair’s activities are definitionally future-oriented, with the ultimate goal being to mitigate as-yet unrealised heritage crime threats before they fully manifest.

The Chair embraces a future-focused and proactive (rather than reactive) view of heritage crime to anticipate problems before they occur and to empower the development of effective policy towards heritage resilience.

Topics of Interest to the Chair

The UNESCO Chair in Cultural Heritage and Emerging crime uses an open definition of both “heritage” and “crime”. Exactly what heritage is now is opaque and what it will be in the future is for us to imagine. Crime too can be see as a shifting grey space outside of the easy definitions of the law. The Chair is open and interested in discussions of grey spaces of the presence and what they mean for our futures.

That said, issues of immediate concern to the proposed Chair include:

  • under-anticipated heritage crime issues related to knock-on effects of climate change;
  • emergence of new forms of heritage (e.g. “born digital” heritage, NFTs) and their susceptibility to crime;
  • mounting uncertainty and heritage crime potential related to world-changing leaps in technological capacity of Artificial Intelligence and Large Language Models.