The Scientific Evidence That Artificial Intelligence (AI) Will Continue to Fail, Until We Deploy ‘Intent’

Electronic machines in the guise of digital computers have transformed our world―social,family,commerce,and politics―although not yet health.Each iteration spawns expectations of yet more astonishing wonders.We wait for the next unbelievable invention to fall into our lap,possibly without limit.How realistic is this?What are the limits,and have we now reached them?A recent survey in The Economist suggests that we have.It describes cycles of misery,where inflated expectations are inevitably followed,a few years later,by disillusion.Yet another Artificial Intelligence(AI)winter is coming―“After years of hype,many people feel AI has failed to deliver”.The current paper not only explains why this was bound to happen,but offers a clear and simple pathway as to how to avoid it happening again.Costly investments in time and effort can only show solid,reliable benefits when full weight is given to the fundamental binary nature of the digital machine,and to the equally unique human faculty of‘intent’.‘Intent’is not easy to define;it suffers acutely from verbal fuzziness―a point made extensively in two earlier papers:“The scientific evidence that‘intent’is vital for healthcare”and“Why Quakerism is more scientific than Einstein”.This paper argues that by putting‘intent’centre stage,first healthcare,and then democracy can be rescued.Suppose every medical consultation were supported by realistic data usage?What if,using only your existing smartphone,your entire medical history were scanned,and instantly compared,within microseconds,with up-to-the-minute information on contraindications and efficacy,from around the globe,for the actual drug you were about to receive,before you actually received it?This is real-time retrieval of clinical data―it increases the security of both doctor and patient,in a way that is otherwise unachievable.My 1980 Ph.D.thesis extolled the merits of digitising the medical record―and,just as digitisation has changed our use of audio and video beyond recognition,so a data-rich medical consultation is unprecedented―prepare to be surprised.This paper has four sections:(1)where binaries help;(2)where binaries ensure extinction;(3)computers in healthcare and civilisation;and(4)data-rich doctoring.Health is vital for economic success,as the current pandemic demonstrates,inescapably.Politics,too,is routinely corrupted―unless we rectify both,failures in AI will be the least of our troubles.

ADAPTIVE REPAIR APPROACH FOR RECOVERING COMPONENTS FROM DEFECTS

The geometry of each worn part is unique, so that a repair has to be tailored to each part individually. To ensure that a high quality repair is carried out, tool paths have to be generated adaptively for the tmique geometry and pose of the part being repaired. A polygonal modelling approach is introduced to rapidly construct a geometric model of the part to be repaired, together with a defect-free model with identical geometry and poise. The two models are compared so that the defects are identified for direct use by the laser cladding, machining and inspection processes.

Semantic 3D City Database—An enabler for a dynamic geospatial knowledge graph

This paper presents a dynamic geospatial knowledge graph as part of The World Avatar project,with an underlying ontology based on CityGML 2.0 for three-dimensional geometrical city objects.We comprehensively evaluated,repaired and refined an existing CityGML ontology to produce an improved version that could pass the necessary tests and complete unit test development.A corresponding data transformation tool,originally designed to work alongside CityGML,was extended.This allowed for the transformation of original data into a form of semantic triples.We compared various scalable technologies for this semantic data storage and chose Blazegraph™as it provided the required geospatial search functionality.We also evaluated scalable hardware data solutions and file systems using the publicly available CityGML 2.0 data of Charlottenburg in Berlin,Germany as a working example.The structural isomorphism of the CityGML schemas and the OntoCityGML Tbox allowed the data to be transformed without loss of information.Efficient geospatial search algorithms allowed us to retrieve building data from any point in a city using coordinates.The use of named graphs and namespaces for data partitioning ensured the system performance stayed well below its capacity limits.This was achieved by evaluating scalable and dedicated data storage hardware capable of hosting expansible file systems,which strengthened the architectural foundations of the target system.

An emotions-informed approach for digital documentation of rural heritage landscapes:Baojiatun,a traditional tunpu village in Guizhou,China

The application of digital technologies has greatly improved the efficiency of cultural heritage documentation and the diversity of heritage information.Yet the adequate incorporation of cultural,intangible,sensory or experimental elements of local heritage in the process of digital documentation,and the deepening of local community engagement,remain important issues in cultural heritage research.This paper examines the heritage landscape of tunpu people within the context of digital conservation efforts in China and the emergence of emotions studies as an evaluative tool.Using a range of data from the Ming-era village of Baojiatun in Guizhou Province,this paper tests an exploratory emotions-based approach and methodology,revealing shifting interpersonal relationships,experiential and praxiological engagement with the landscape,and emotional registers within tunpu culture and heritage management.The analysis articulates distinctive asset of emotional value at various scales and suggests that such approaches,applied within digital documentation contexts,can help researchers to identify multi-level heritage landscape values and their carriers.This methodology can provide more complete and dynamic inventories to guide digital survey and representation;and the emotions-based approach also supports the integration of disparate heritage aspects in a holistic understanding of the living landscape.Finally,the incorporation of community participation in the process of digital survey breaks down boundaries between experts and communities and leads to more culturally appropriate heritage records and representations.