Lecture 10: Decision making using AI Flashcards
(8 cards)
What is AI? (p218-219)
- “….in general, it means a program using data to build a model of some aspect of the world. This model is then used to make informed decisions and predictions about future events” (p218)
- Machine learning is an application of AI that enables computers systems to automatically learn, adapt and improve experience and pattern recognition – without being explicitly programmed by a human being” (p218)
- AI technology raises serious social, ethical, and political concerns (p218)
- ‘Generative’ AI
- Machine learning
- Artificial neural networks
AI Safety Summit (1)
AI presents enormous global opportunities: it has the potential to transform and enhance human well-being, peace and prosperity. To realise this, we affirm that, for the good of all, AL should be designed, developed, deployed and used, in a manner that is safe, in such a way to as to be human-centric, trustworthy, and responsible (p35).
“….to be used for the good of all, in an inclusive manner in our countries and globablly. This includes for public services such as health and education, food security, in science, clean energy, biodiversity, and climate, to realise the enjoyment of human rights, and to strengthen efforts towards achievement of the UN Sustainable Development Goals (SDG’s) (November 2023)
AI Safety Summit (2)
- AI also poses significant risks: including in those domains of daily life….and the recognition that the protection of human rights, transparency and explainability, fairness, accountability, regulation, safety, appropriate human oversight, ethics, bias mitigation, privacy and data protection needs to be addressed.
- We also note the potential for unforeseen risks stemming from the capability to manipulate context of generative deceptive content.
- AI systems may amplify risks such as disinformation
- Many risks arising from AI are “inherently international in nature” (p35)
Where does AI play a role in organizational decision-making?
- Healthcare (e.g. NHS24)
- Policing (profiling)
- Education
- Banking (loan and mortgage applications)
- Investment
- Digital marketing strategy
- Retail (supermarket loyalty cards)
- Social media (tracking your video streaming)
- Music streaming (Apple Music et al)
- Generative AI (Google Bard, Chat GPT et al)
- The broad and widescale use of algorithms
Merits of AI (from its proponents)
- Diagnosis of illness +++
- Consistency of decision-making in financial and borrowing decisions
- Contributions to housing etc
- Personal safety (e.g. GPS)
- Most recent advances in AI attempt a single, hybrid AI model
Improving work efficiency
Reducing costs
Better decision making
Improving product quality
Optimizing human resources structure
Creating new jobs
Limitations of AI (from experience to date)
- Regional accents and local knowledge (
- How could AI ‘do’ Evidence-Based Management?
- How could it help manage stakeholders? (Recall Hodgkinson et al, 2012)
- The technological expression of emotion is not the same as experienced human feeling
- Cybersecurity, bioethics, non-consenting of data sharing etc.
- It cannot predict some unforeseen events e.g. 9/11, 2008 financial crash, COVID-19
Lack of human judgment and creativity – AI lacks intuition, emotions, and the ability to think abstractly or creatively like humans.
High development costs – Designing, training, and maintaining AI systems can be very expensive.
Data dependency – AI systems require vast amounts of high-quality data to function effectively.
Limited generalization – Most AI is good at specific tasks but cannot transfer learning to unrelated problems.
Job displacement – Automation by AI may lead to unemployment in certain sectors.
Ethical concerns – Issues like bias in algorithms, lack of transparency, and decision accountability are serious concerns.
Security risks – AI systems can be vulnerable to hacking, misuse, or adversarial attacks.
Lack of emotional intelligence – AI cannot understand or respond to human emotions with empathy.
Legal and regulatory uncertainty – The law is still catching up with the pace of AI development, leading to unclear responsibilities and liabilities.
Over-reliance risk – Excessive dependence on AI may reduce human skill development and oversight.
Ethical decision-making & AI
- Depends on the ethics of data inserter(s), and the strategic purpose of the organization, and what regulators permit
- There is evidence +++ where AI is not ethical (either by intent, or default)
- Gender and racial bias evidence is confirmed from studies +++
- How can AI models created by organizations, for their own benefit, be more mindful of ethical factors?
Risks adopting AI in decision-making (1)
- Loss of jobs and the disposability of human labour
- Conflicting perspectives : IMF Report (2024) v Andrew Bailey (Governor Bank of England, 2023)
- “In most scenarios, AI will likely worsen overall equality” (IMF Report,15 Jan.24)
- “AI will not be a mass destroyer of jobs” (2nd Feb.24)
