Artificial intelligence accompanies big data bring major risk and dangers to society. Understanding threats is a key to make the technolog and data work for our good,

1. Dangers of AI and big data
Piotr Poznański

2. ”Artificial intelligence
(visions of the future)

3. Terminator (1984)

4. Screamers (1995)

5. Mass Effect

6. ”Artificial intelligence
(AD 2018)

7. AI story begins in 1956
AI, Deep Learning, and Machine Learning: A Primer (45 min)
https://a16z.com/2016/06/10/ai-deep-learning-machines/

8. Neural networks

9. Image recognition
(Google Cloud Vision API)
Neural networks
Reasoning
(Apha Go)
Natural language processing
(Google Home, Amazon Alexa)

10. Facebook VP & Chief AI Scientist LeCun on Advancing AI
https://youtu.be/dzQRCZyE4v0

11. ” Danger #1
Profiling in political consulting/marketing

12. Filter bubble and democracy
https://www.ted.com/talks/eli_pariser_beware_online_filter_bubbles

13. Message profiling example
I will take care of animal shelters
and feeding of homeless animals
I will utterly solve a problem of
stray dogs and animal poop on
the sidewalks
http://wyborcza.pl/7,162657,23314217,o-cambridge-analytica-lopatologicznie.html

14. Cambridge Analytica Files
https://www.theguardian.com/news/series/cambridge-analytica-files

15. Voice profiling

16. ” Danger #2
Bias → discrimination

17. Input data (historic bias)

18. Input data (manipulation)
https://www.theverge.com/2016/3/24/11297050/tay-microsoft-chatbot-racist

19. Input data (bias)
https://www.ted.com/talks/joy_buolamwini_how_i_m_fighting_bias_in_algorithms

20. Input data (bias)
https://www.technologyreview.com/s/611138/microsoft-is-creating-an-oracle-for-catching-biased-ai-algorithms/
“The most important thing companies can do right now is
educate their workforce so that they’re aware of the myriad
ways in which bias can arise and manifest itself and create
tools to make models easier to understand and bias easier
to detect”
Rich Caruna
Microsoft

21. ” Danger #3
Trust

22. https://www.theverge.com/2018/1/24/16929148/fake-celebrity-porn-ai-deepfake-face-swapping-artificial-intelligence-reddit
http://www.bbc.com/news/av/technology-40598465/fake-obama-created-using-ai-tool-to-make-phoney-speeches
Face manipulation (deep fakes)

23. ” Danger #4
Mechanistic trust

24. How neural networks works | least squares method

25. How neural networks works

26. Neural networks limitations
● Correlation not causation
● Do not reveal deep (physical) nature of
phenomenons
● Is not auditable
● Is prone to bias
○ input data
○ subject of research
Luck of understanding of AI limitations
may lead to mechanistic trust and
application of AI driven research results
Data Science as Mechanic Neoplatonism by Dan McQuillan
https://link.springer.com/article/10.1007%2Fs13347-017-0273-3