速度还是方向:人工智能时代的哲学考察

人工智能是人类复杂性的程序化产物,它不会全面替代人类。人工智能的潜在威胁不是它在专业能力上的迅猛发展,而是它的资本主义应用及不平等的极化发展。应对这一威胁的正确方式不是要追赶人工智能的发展速度,而是要干预人工智能的发展方向。不同的干预会导致不同的后果。就消除不合理的不平等而言,出路之一是进行数字化社会主义干预。这一干预在动力源上强调人类不可程序化的激情、顿悟、灵感等的重要性,施行社会主义共享精神教育;在所有权上主张数据的公有化,建构数据平台三权分置的所有权制度;在分配原则上主张全民基本收入。这一干预有可能导致人工智能时代数字社会主义的诞生,并且根本上影响数字社会主义的发展方向。

Reasoning complexity for extended fuzzy description logic with qualifying number restriction

To solve the extended fuzzy description logic with qualifying number restriction （EFALCQ） reasoning problems, EFALCQ is discretely simulated by description logic with qualifying number restriction （ALCQ）, and ALCQ reasoning results are reused to prove the complexity of EFALCQ reasoning problems. The ALCQ simulation method for the consistency of EFALCQ is proposed. This method reduces EFALCQ satisfiability into EFALCQ consistency, and uses EFALCQ satisfiability to discretely simulate EFALCQ satdomain. It is proved that the reasoning complexity for EFALCQ satisfiability, consistency and sat-domain is PSPACE-complete.