Conclusions

Unchecked/unregulated data usage, specifically by large corporations, can be extremely dangerous and detrimental to the public.

      Potential Data Breaches: 

1. In the movie, the Terminator breaks into the Rathium Data Center and manages to gain access to private information, along with security camera footage [6]. Although this may seem like it's just science fiction, modern data breaches are actually very common. Just in 2023, a T-Mobile data breach leaked the information of 37 million users, the data included driver's license information and social security numbers [3]. This was just one of 3 data leaks T Mobile had that year.

2. Global Surveillance Statistics: According to a report by Privacy International, over 176 million video surveillance cameras are installed worldwide. In the United States alone, there are approximately 50 million surveillance cameras, according to estimates by the American Civil Liberties Union (ACLU).

3. Data Breach Statistics: In 2023, the global average data breach cost was $4.24 million [1­­­­]. Furthermore, the number of ransomware attacks increased by 318.6 million in 2021, a 105% increase compared to 2020, underscoring cybersecurity threats’ significant financial and reputational consequences [2]. 

    Data Misuse: 

1. Cambridge Analytica harvested the personal data of 50-87 million Facebook users without their consent [4]. This data was used to target and manipulate voters during the 2016 U.S Presidential election to support the Trump campaign. The misuse of complex technologies, and data in both the real-life scenario of the Cambridge and the fictional Terminator: Dark Fate scenario, can have significant consequences. The over-cultivation of data, and furthermore the misuse of large datasets, can lead to dire situations and can put large portions of the general public at risk.

References: 

1.   IBM, Cost of a Data Breach Report 2023, (IBM, 2023) https://www.ibm.com/reports/data-breach (April 16th, 2024)

2. SonicWall, SonicWall Threat Intelligence Confirms Alarming Surge in Ransomware, Malicious Cyberattacks as Threats Double in 2021, (SonicWall, 2022)  https://www.sonicwall.com/news/sonicwall-threat-intelligence-confirms-alarming-surge-in-ransomware-malicious-cyberattacks-as-threats-double-in-2021/#:~:text=Ransomware's%20Savage%20Reign%20Continues%20as,has%20risen%20232%25%20since%202019. (April 16th, 2024)

3. T Mobile Data breach class Action Lawsuit https://www.t-mobilesettlement.com/home/1552/DocumentHandler?docPath=/Documents/1_01_Consolidated_Consumer_Class_Action_Complaint.pdf (April 17th, 2024).

4.  Katie Harbath, “History of the Cambridge Analytica Controversy”, https://bipartisanpolicy.org/blog/cambridge-analytica-controversy/#:~:text=Cambridge%20Analytica%20claimed%20to%20be,fully%20shut%20down%20in%202015 .(April 16, 2023)

5. Alvin Chang, “The Facebook and Cambridge Analytica scandal, explained with a simple diagram” (Vox, May 2, 2018) https://www.vox.com/policy-and-politics/2018/3/23/17151916/facebook-cambridge-analytica-trump-diagram (May 2nd, 2018)

6. Miller, T. (2019). Terminator: Dark Fate. Paramount Pictures. (0:46:23)

Dangers of overreliance on artificial intelligence (AI) and the potential consequences of allowing AI to wield unchecked power. 

Loss of Human Control: 

1. The film depicts a future where advanced AI, such as Legion, has gained control over military forces and autonomous killing machines. This scenario raises concerns about the loss of human control and oversight in decision-making processes. 

2. According to a study by Oxford University, 47% of U.S. jobs are at risk of automation in the next few decades, highlighting the potential societal impact of AI-driven automation on employment and economic stability. [1]

3. The reliance on AI for critical decision-making in finance, healthcare, and criminal justice sectors raises ethical questions about accountability, transparency, and bias in algorithmic decision-making processes. 

4. Predictive policing systems unfairly target minorities; black people are twice as likely to be arrested and five times more likely to be stopped than white people, according to the US Department of Justice . [7] 

5. AI used to prioritize patient care is less likely to refer minority patients; black patients are 80% less likely to receive extra help than white patients, even when the algorithm assigned similar risk scores. [8]

Unintended Consequences and Errors:

1. The actions of Legion in the film show the potential for unintended consequences when AI systems operate without human intervention

2. Research by McKinsey Global Institute found that AI systems can exhibit biases and inaccuracies. Disproportionately affecting certain groups or individuals. COMPAS, a tool used to predict recidivism in Broward County, Florida, incorrectly labeled African American defendants as "high-risk" at nearly twice the rate it mislabeled white defendants [2]. Also, scientists at MIT, at the time Microsoft, found that women with darker skin had misclassification rates of 20.8%-34.7%, compared to error rates of 0.0%-0.8% for men with lighter skin using algorithms developed by Microsoft, Face++, and IBM [5]. In 2018, Amazon discarded its proprietary AI recruiting tool because the data that it was trained on was majority male, which made it systematically biased against women. [6]

3. The movie showed the Rev-9 terminator as having a single-minded goal of completing its mission without consideration for collateral damage, showing the potential dangers of AI systems prioritizing objectives over moral/ethical considerations.

Threats to Privacy and Autonomy:

1. The expansion of AI-based surveillance systems, as depicted in the film, poses threats to privacy and individual autonomy. Unregulated data collection and AI-driven analysis can suppress privacy rights and create a surveillance state where individuals are constantly being monitored and judged. Effect on mental health. In 2012, Finish researchers looked at the effects of continuous computerized surveillance on individuals. This revealed that 90% of the participants noted a sense of annoyance, anxiety, and even anger. This number highlights the mental health risk of implementing facial recognition surveillance.  [3]

2. A study by Amnesty International found that facial recognition technology poses significant risks to human rights, including the right to privacy, freedom of expression, and freedom of assembly [4]. 

3. The movie showed the Rev-9 terminator transforming into different humans through touch. This could show issues related to privacy issues and how fake information should be shared due to AI. It is further explored when the Terminator hacked into the Rathium Data Center, Mexico City, to get the location of a single person, Dani Ramos.

4. This can be explicitly seen in China, where the government had brainwashed the people to accept surveillance their loss of privacy [9]. The most devastating example of the loss of privacy could be seen with surveilance of Muslims, who are an ethnic minority, in Xinjiang [9].

References: 

1. Michael Osborne & Carl Benedikt Frey, “Automation and the future of work – understanding the numbers,” (Oxford Martin School, April 13th, 2018), https://www.oxfordmartin.ox.ac.uk/blog/automation-and-the-future-of-work-understanding-the-numbers/ (April 16th, 2024)

2.  Jake Silberg & James Manyika, “Tackling bias in artificial intelligence (and in humans),”  (McKinsey & Company, June 6th, 2019), https://www.mckinsey.com/featured-insights/artificial-intelligence/tackling-bias-in-artificial-intelligence-and-in-humans (April 16th, 2024)

3. Saumya Kalia, “What Is a Constant Lack of Digital Privacy Doing to Our Mental Health?”, (The SWDL, January 26th, 2022), https://www.theswaddle.com/what-is-a-constant-lack-of-digital-privacy-doing-to-our-mental-health (April 16th, 2024)

4.  “Ban dangerous facial recognition technology that amplifies racist policing”, (Amnesty International, January 26th, 2021), https://www.amnesty.org/en/latest/press-release/2021/01/ban-dangerous-facial-recognition-technology-that-amplifies-racist-policing/ (April 16th, 2024)

5. Joy Buolamwini & Timnit Gebru, “Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification” , (MLR, 2018) https://proceedings.mlr.press/v81/buolamwini18a/buolamwini18a.pdf (April 16th 2024)

6. Jeffrey Dastin, "Insight - Amazon scraps secret AI recruiting tool that showed bias against women" (Reuters, October 10, 2018), https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G/ (April 18th, 2024)

7. Will Douglas Heaven, “Predictive policing algorithms are racist. They need to be dismantled.”, (MIT Technology Review, July 17th, 2020), https://www.technologyreview.com/2020/07/17/1005396/predictive-policing-algorithms-racist-dismantled-machine-learning-bias-criminal-justice/ (April 18th, 2024)202

8. TOM SIMONITE, "A Health Care Algorithm Offered Less Care to Black Patients" (Wired, October 29th, 2024) https://www.wired.com/story/how-algorithm-favored-whites-over-blacks-health-care/ (April 18th, 2024)

9. Zeyi Yang, The Chinese surveillance state proves that the idea of privacy is more “malleable” than you’d expect, (MIT Techonology Review, October 10th, 2022), https://www.technologyreview.com/2022/10/10/1060982/china-pandemic-cameras-surveillance-state-book/ (April 22, 2024)

10. Carl Benedikt Frey and Michael A. Osborne, “THE FUTURE OF EMPLOYMENT: HOW SUSCEPTIBLE ARE JOBS TO COMPUTERISATION? “(September 17, 2013), https://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf (April 16th, 2024)

11. Muyi Xiao, Paul Mozur, Isabelle Qian and Alexander Cardia, “China’s Surveillance State Is Growing. These Documents Reveal How.” https://www.nytimes.com/video/world/asia/100000008314175/china-government-surveillance-data.html (April 22, 2024)

12. Miller, T. (2019). Terminator: Dark Fate. Paramount Pictures. (1:23:51)

13. Miller, T. (2019). Terminator: Dark Fate. Paramount Pictures. (1:26:06)