59
Views
0
CrossRef citations to date
0
Altmetric
Abstract

Humans and machine: computer-assisted consensus amongst forensic examiners

Pages 191-196 | Received 29 Feb 2024, Accepted 29 Feb 2024, Published online: 28 Apr 2024

References

  • Alowais SA, Alghamdi SS, Alsuhebany N, Alqahtani T, Alshaya AI, Almohareb SN, Aldairem A, Alrashed M, Bin Saleh K, Badreldin HA, et al. Revolutionizing healthcare: the role of artificial intelligence in clinical practice. BMC Med Educ. 2023;23(1):689. doi:10.1186/s12909-023-04698-z
  • Lee LI, Kanthasamy S, Ayyalaraju RS, Ganatra R. The current state of artificial intelligence in medical imaging and nuclear medicine. BJR| Open. 2019;1(1):20190037. doi:10.1259/bjro.20190037
  • Connon ILC, Egan M, Hamilton-Smith N, MacKay N, Miranda D, Webster CWR. Review of emerging technologies in policing: findings and recommendations. Edinburgh: Scottish Government; 2023 [accessed 2024 Feb 29]. https://discovery.dundee.ac.uk/ws/portalfiles/portal/98288751/review_emerging_technologies_policing_report_1_.pdf
  • Galante N, Cotroneo R, Furci D, Lodetti G, Casali MB. Applications of artificial intelligence in forensic sciences: Current potential benefits, limitations and perspectives. Int J Legal Med. 2023;137(2):445–458. doi:10.1007/s00414-022-02928-5
  • Sushina T, Sobenin A. Artificial intelligence in the criminal justice system: leading trends and possibilities. In: 6th International Conference on Social, economic, and academic leadership (ICSEAL-6-2019), Prague (Czech Republic). Atlantis Press; 2020.
  • Lai V, Chen C, Liao QV, Smith-Renner A, Tan C. Towards a science of human-ai decision making: a survey of empirical studies. arXiv Preprint arXiv: 2112.11471. 2021.
  • Gruetzemacher R, Dorner FE, Bernaola-Alvarez N, Giattino C, Manheim D. Forecasting AI progress: a research agenda. Technol Forecast Soc. 2021;170:120909. doi:10.1016/j.techfore.2021.120909
  • Soori M, Arezoo B, Dastres R. Artificial intelligence, machine learning and deep learning in advanced robotics, a review. Cognit Rob. 2023;3:54–70. doi:10.1016/j.cogr.2023.04.001
  • Mansoor N, Iliev A. Artificial Intelligence in Forensic Science. In: Future of Information and Communication Conference, Virtual Event. Springer; 2023.
  • Kahneman D, Klein G. Conditions for intuitive expertise: a failure to disagree. Am Psychol. 2009;64(6):515. doi:10.1037/a0016755
  • Kahneman D. Thinking, fast and slow. UK: Macmillan; 2011.
  • Liu P, Du Y, Xu Z. Machines versus humans: People’s biased responses to traffic accidents involving self-driving vehicles. Accident Anal Prev. 2019;125:232–240. doi:10.1016/j.aap.2019.02.012
  • Xu Y, Liu X, Cao X, Huang C, Liu E, Qian S, Liu X, Wu Y, Dong F, Qiu C-W, et al. Artificial intelligence: A powerful paradigm for scientific research. Innov. 2021;2(4):100179. doi:10.1016/j.xinn.2021.100179
  • Gibb C, Riemen J. Toward better AFIS practice and process in the forensic fingerprint environment. Forensic Sci Int: Synergy. 2023;7:100336. doi:10.1016/j.fsisyn.2023.100336
  • Stokes D. On perceptual expertise. Mind Lang. 2021;36(2):241–263. doi:10.1111/mila.12270
  • Dunn JD, Towler A, Kemp RI, White D. Selecting police super-recognisers. PLoS One. 2023;18(5):e0283682.
  • Park H, Megahed A, Yin P, Ong Y, Mahajan P, Guo P. Incorporating experts’ judgment into machine learning models. Expert Syst Appl. 2023;228:120118. doi:10.1016/j.eswa.2023.120118
  • Phillips PJ, O’toole AJ. Comparison of human and computer performance across face recognition experiments. Image Vis Comput. 2014;32(1):74–85. doi:10.1016/j.imavis.2013.12.002
  • Growns B, Martire KA. Human factors in forensic science: the cognitive mechanisms that underlie forensic feature-comparison expertise. Forensic Sci Int: Synergy. 2020;2:148–153. doi:10.1016/j.fsisyn.2020.05.001
  • Busey T, Dror IE. Special abilities and vulnerabilities in forensic expertise. Washington, DC: Friction Ridge Sourcebook. NIJ Press; 2011.
  • Dror IE, Mnookin JL. The use of technology in human expert domains: challenges and risks arising from the use of automated fingerprint identification systems in forensic science. Law Probab Risk. 2010;9(1):47–67. doi:10.1093/lpr/mgp031
  • Gibb C, White AV. Examination of friction ridge impressions. In: Encyclopedia of forensic sciences. 3rd ed. US: Elsevier; 2023. p. 316–327.
  • Dror IE, Champod C, Langenburg G, Charlton D, Hunt H, Rosenthal R. Cognitive issues in fingerprint analysis: inter- and intra-expert consistency and the effect of a ‘target’ comparison. Law Probab Risk. 2011;208(1–3):10–17. doi:10.1016/j.forsciint.2010.10.013
  • Ulery BT, Hicklin RA, Roberts MA, Buscaglia J. Interexaminer variation of minutia markup on latent fingerprints. Forensic Sci Int. 2016;264:89–99. doi:10.1016/j.forsciint.2016.03.014
  • Hicklin RA, Ulery BT, Ausdemore M, Buscaglia J. Why do latent fingerprint examiners differ in their conclusions? Forensic Sci Int. 2020;316:110542. doi:10.1016/j.forsciint.2020.110542
  • Ulery BT, Hicklin RA, Buscaglia J, Roberts MA. Accuracy and reliability of forensic latent fingerprint decisions. Proc Natl Acad Sci USA. 2011;108(19):7733–7738. doi:10.1073/pnas.1018707108
  • Eldridge H, De Donno M, Champod C. Testing the accuracy and reliability of palmar friction ridge comparisons–a black box study. Forensic Sci Int. 2021;318:110457.
  • Carr S, Piasecki E, Gallop A. Demonstrating reliability through transparency: a scientific validity framework to assist scientists and lawyers in criminal proceedings. Forensic Sci Int. 2020;308:110110. doi:10.1016/j.forsciint.2019.110110
  • Stoney DA, Stoney PL. Utility of non-identifiable fingermarks. Forensic Sci Int. 2021;319:110630. doi:10.1016/j.forsciint.2020.110630
  • Eldridge H, De Donno M, Girod M, Champod C. Coping With Close Non-Matches In Latent Print Comparison (Re-)Training. 2023 [accessed 2023 Mar 24] CNMs. Available from: https://www.ojp.gov/pdffiles1/nij/grants/305757.pdf
  • Eldridge H, DeDonno M, Furrer J, Champod C. Examining and expanding the friction ridge value decision. Forensic Sci Int. 2020;314:110408. doi:10.1016/j.forsciint.2020.110408
  • Champod C, Lennard CJ, Margot P, Stoilovic M. Fingerprints and other ridge skin impressions. 2nd ed. CRC press; 2017.
  • Ulery BT, Hicklin RA, Roberts MA, Buscaglia J. Measuring what latent fingerprint examiners consider sufficient information for individualization determinations. PloS One. 2014;9(11):e110179. doi:10.1371/journal.pone.0110179
  • Dror IE, Langenburg G. “Cannot decide”: the fine line between appropriate inconclusive determinations versus unjustifiably deciding not to decide. J Forensic Sci. 2019;64(1):10–15. doi:10.1111/1556-4029.13854
  • Swofford HJ, Koertner AJ, Zemp F, Ausdemore M, Liu A, Salyards MJ. A method for the statistical interpretation of friction ridge skin impression evidence: method development and validation. Forensic Sci Int. 2018;287:113–126. doi:10.1016/j.forsciint.2018.03.043
  • Langenburg G, Champod C, Genessay T. Informing the judgments of fingerprint analysts using quality metric and statistical assessment tools. Forensic Sci Int. 2012;219(1–3):183–98. doi:10.1016/j.forsciint.2011.12.017
  • Kahneman D, Sibony O, Sunstein CR. Noise: a flaw in human judgment. UK: HarperCollins; 2021.
  • Tangen JM, Kent KM, Searston RA. Collective intelligence in fingerprint analysis. cognitive research: principles and implications. Cognit Res: Princ Implic. 2020;5(1):1–7. doi:10.1186/s41235-020-00223-8
  • Swofford H, Champod C. Implementation of algorithms in pattern & impression evidence: a responsible and practical roadmap. Forensic Sci Int. 2021;3:100142. doi:10.1016/j.fsisyn.2021.100142
  • UNIL. PiAnOs documentation. 2021 [accessed 2020 Oct 25]. Available from: https://ips-labs.unil.ch/doc/
  • Egli NM. Interpretation of Partial Fingermarks Using an Automated Fingerprint Identification System [ Ph.D. Dissertation, School of Criminal Justice, Faculty of Law and Criminal Sciences]. Lausanne; University of Lausanne; 2009 [accessed 2024 Mar 12].https://serval.unil.ch/resource/serval:BIB_25F6DAD7F893.P001/REF.pdf

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.