Deception-detection and machine intelligence in practical Turing tests

Deception-detection is the crux of Turing’s experiment to examine machine thinking conveyed through a capacity to respond with sustained and satisfactory answers to unrestricted questions put by a human interrogator. However, in 60 years to the month since the publication of Computing Machinery and Intelligence little agreement exists for a canonical format for Turing’s textual game of imitation, deception and machine intelligence. This research raises from the trapped mine of philosophical claims, counter-claims and rebuttals Turing’s own distinct five minutes question-answer imitation game, which he envisioned practicalised in two different ways: a) A two-participant, interrogator-witness viva voce, b) A three-participant, comparison of a machine with a human both questioned simultaneously by a human interrogator. Using Loebner’s 18th Prize for Artificial Intelligence contest, and Colby et al.’s 1972 transcript analysis paradigm, this research practicalised Turing’s imitation game with over 400 human participants and 13 machines across three original experiments. Results show that, at the current state of technology, a deception rate of 8.33% was achieved by machines in 60 human-machine simultaneous comparison tests. Results also show more than 1 in 3 Reviewers succumbed to hidden interlocutor misidentification after reading transcripts from experiment 2. Deception-detection is essential to uncover the increasing number of malfeasant programmes, such as CyberLover, developed to steal identity and financially defraud users in chatrooms across the Internet. Practicalising Turing’s two tests can assist in understanding natural dialogue and mitigate the risk from cybercrime.

Eight-plex iTRAQ analysis of variant metastatic human prostate cancer cells identifies candidate biomarkers of progression: an exploratory study.

BACKGROUND: Due to the heterogeneity in the biological behavior of prostate cancer, biomarkers that can reliably distinguish indolent from aggressive disease are urgently needed to inform treatment choices. METHODS: We employed 8-plex isobaric Tags for Relative and Absolute Quantitation (iTRAQ), to profile the proteomes of two distinct panels of isogenic prostate cancer cells with varying growth and metastatic potentials, in order to identify novel biomarkers associated with progression. The LNCaP, LNCaP-Pro5, and LNCaP-LN3 panel of cells represent a model of androgen-responsive prostate cancer, while the PC-3, PC-3M, and PC-3M-LN4 panel represent a model of androgen-insensitive disease. RESULTS: Of the 245 unique proteins identified and quantified (>or=95% confidence; >or=2 peptides/protein), 17 showed significant differential expression (>or=+/-1.5), in at least one of the variant LNCaP cells relative to parental cells. Similarly, comparisons within the PC-3 panel identified 45 proteins to show significant differential expression in at least one of the variant PC-3 cells compared with parental cells. Differential expression of selected candidates was verified by Western blotting or immunocytochemistry, and corresponding mRNA expression was determined by quantitative real-time PCR (qRT-PCR). Immunostaining of prostate tissue microarrays for ERp5, one of the candidates identified, showed a significant higher immunoexpression in pre-malignant lesions compared with non-malignant epithelium (P < 0.0001, Mann-Whitney U-test), and in high Gleason grade (4-5) versus low grade (2-3) cancers (P < 0.05). CONCLUSIONS: Our study provides proof of principle for the application of an 8-plex iTRAQ approach to uncover clinically relevant candidate biomarkers for prostate cancer progression.