Maria Johnsen talks about risk assessment and security aspects of artificial intelligence and machine learning.
In recent years, the use of Artificial Intelligence has peaked. Decisions may be at risk if they are made by a machine. Artificial intelligence can be economically disastrous and liable equally due to various thought-provoking aspects of the situation. Experts hold the opinion that there is a liability risk if the Machines make decisions which are rather inappropriate or illegal.
According to Maria Johnsen in fintech and banking systems the rules on risk management describe how models should be validated, but these rules do not cover A.I and machine learning algorithms. With predictive models, they build the model and test it. But they don’t test to see if the algorithm changes based on the data they feed it. In machine learning, the algorithms change, evolve and grow; at the same time, new biases could potentially be added.
Regulators should be finding solutions to the risks of machine learning models. For example, in loan decision making, the data could inform an unconscious bias against minorities that could expose the bank to regulatory scrutiny.
Machine Learning Problems:
The risks associated with Artificial Intelligence and machine learning can be potentially dangerous if not managed timely. Following are some of the main risks associated with this phenomenon:
- Data:The pedigree of the data used to create machines is largely involved in the risk. The variability in the amount of the data determines how it would run in the long term. This is why it should be a homogenous data.
- Bias:It can be a source of inaccuracy in the models which can make the data highly inaccurate.
- Output Interpretation:The use and the way a model is interpreted can undoubtedly add to the risk.
If you train an algorithm with data that has underlying racist data, you may end up making a racist machine learning algorithm. We need to step back before we all jump on the bandwagon.
AI is used in various aspects of programming that include finding solutions to a problem and recognizing patterns. In machine learning, a computer program is given access to a huge amount of data and then it processes that information. This is how it learns the relationship between variables.
For more information read her entire article at A.I and Machine Learning
About Maria Johnsen
Maria Johnsen is a Multilingual Digital Marketing A.I and Fintech Influencer, Film producer , director, screenwriter,Linguist and author. She holds a degree in political economy from Kharkov University in Ukraine, Beauty Arts from Sorbonne University in Paris, BA in Information technology, BA in computer science, a Master of Science degree in computer engineering from university of science and technology in Norway and master degree in filmmaking and television from Royal Holloway University of London.
Her professional background and education is diverse and includes skills in areas such as sales, multilingual digital marketing, content writing, business intelligence, software design and development. In addition, she possesses the experience and education in the management of complex Information Systems.
Maria knows eighteen languages and possesses experience in language instruction, tutoring, and translation. She has also developed a unique teaching method for fast learning “Implications for Upgrading Accelerated Learning Practices In Educational Systems” This method is applied in China and Norway.
Maria Johnsen is also a multilingual SEO, PPC and social media marketing expert. She managed software projects for well known IT companies and Bank in Norway, China, the UK as well as cooperation with governments and police authorities in regards to projects related to data crime and tracing terrorists online.
Starting in 2008, she began offering search engine optimization services. Her company Golden Way Media expanded internationally in 2009 carrying out various projects in Europe, North America and Asia. While offering services to the general public, Maria Johnsen continues to consult with corporate clients, agencies and small businesses. She has skills and proven records in all areas of search engine optimization including keyword targeting, competitor research and on-site optimization.