Challenges to Society by Dig Data and Algorithms
In recent years, the development of Internet, smart cars, wearable devices and Cloud technology, have led to the rapid growth of data in almost all industry and business areas. Big data has rapidly developed into a hot topic which had attracted extensive attention from academia, industry, and also governments internationally. With this comes major impacts on society- from how individuals shop, interact socially, obtain information to how large companies do business in terms of consumer research, recruitment and policy. Is this just the new convention in society? An algorithm is a series of instructions, like a flowchart or a food recipe, which can be followed to solve a specific problem. Surely technological advancements can only mean progression and with this social justice? There is evidence to suggest otherwise, with some critics such as Cathy O’ Neil (2016) stating they provide “a model that contributes to a toxic cycle and helps to sustain it.” In terms of data produced via our digital lives – does anyone really collect the private information that we unwittingly disseminate, or is Big Brother really and truly out there? Is there an ethical obligation on digital companies to be more explicit about what information they collect and what they do with it, now, or in the future? Should we change how we behave to protect our privacy? Or has society adapted to their presence so much that there are no alternatives, are we “locked in” to their usage? Algorithms are routinely employed in the United States criminal justice system to predict the likelihood that a prisoner will reoffend after release. The Level of Service Inventory Revised (LSIR) questionnaire uses a number of socioeconomic factors in its calculations, such as social class, level of education, place of residence. How such factors are used in the algorithm is, according to O’Neil (2016), very opaque. Prisoners are unaware of what their answers will implicate. The algorithm appears to disadvantage those from a poor socio-economic background. For example, one of the questions asks about close contacts and their history with law enforcement: for those in ghetto areas , it is almost inevitable that there is some previous involvement. These responders are flagged as high-risk, not necessarily because of factors that actually contribute to increased recidivism, leading to the “pernicious feedback loop” of which O’Neil (2016) speaks. Although it is argued by those that support the method that it will decrease the sentencing lengths for the non-threatening criminals, it can pre-condemn the already disadvantaged within society. The risk scores are seen by the sentencing judges and guide them in their decisions. Furthermore, prisoners do not know their risk scores as there is no transparency and prisoner officials do not reveal the purposes of the LSIR questionnaire. The apparent aim of such a process is to “bring even-handedness and efficiency to the criminal justice system’ (O’Neil 2016). The use of this recidivism model speeds up the sentencing process for the judges and saves the tax payer money, in a society where the criminal justice system costs eighty million per year. It is understandable, but, is it worth it if people are being discriminated against because of their social background? So, since this model saves a substantial amount of time and money and prisoners do not share the same rights as the rest of society will this ever change? Probably not. However, the appeared effectiveness of these “weapons of maths destruction” within the prison system, as argued by O’Neil (2016) could lead to the spread of these mathematical models throughout the economy and society, leaving the public as collateral damage. Algorithms have been used in recruitment utilised mainly to speed up the process; reducing initial applicant numbers to more manageable amounts without human intervention. Companies use intelligent and personality tests to decrease the number of applicants in moving to the interview process. However, as O’Neil (2016) puts it, these tests have been known to be discriminatory. In Griggs vs Duke Power Co. (1971), the Duke Power Company used intelligent tests in their recruitment process, proxies which were found to be discriminatory and illegal by the Supreme Court. Subsequently, intelligent tests were replaced with personality tests, which have been identified as poor predictors of job performance (Murphy, 2005). Their aim is not to determine the best employees for the job but to exclude undesirable candidates, thus saving the companies time and money. O’Neil (2016) argues that personality tests could be valuable if used in an appropriate way, for example, with the purpose of educating workers on their behaviours, or to improve communication and teamwork. Supporters of these tests claim that no one answer will disqualify an applicant but the lack of transparency is a problem: applicants do not know what patterns are being measured or why, and do not receive feedback. Kyle Blehm’s story exemplifies the challenges with such algorithms. Blehm, a high-academic achiever elected to break from his college studies due to a new diagnosis of bipolar disease. His attempts to pass multiple entry tests in low-income roles were unsuccessful, leading to his father, a lawyer, filing a class action suit against the companies for discriminating against his son due to his mental health. Most people applying for such roles do not have the resources to do this however; the “pernicious feedback loop” manifests again. Disadvantaged work-seekers have fewer employment choices so must acquiesce to a company’s requirements. People from lower socio-economic groups have less education and higher health issues, all of which can be identified in these tests in ways which would be difficult to ascertain without the algorithms, thus preventing progression and perpetuating inequality. One of the ways that algorithms perpetuate social inequality is by becoming automated versions of human bias. St. George’s Hospital, London used a data process , the algorithm for which was formed from rules applied to previous applicants, which when manually reviewed was subject to unconscious bias. For example, CVs with grammatical errors or names similar to those of unsuccessful applicants were discarded in the manual shortlisting: this rule was also applied in the algorithms. Thus, a major challenge is that an algorithm may have the characteristics of the person who designs and inputs the information. In 1988 the medical school was found guilty of racial and gender inequality in their recruitment process. The school then removed the gender, race, and geographical proxies and only used relevant medical education data. As O’Neil (2016) puts it, the person’s own values and desires influence our choices. Whoever builds or designs these algorithms have an objective and unfortunately those opinions and objectives get rooted into the algorithm. “Mathwashing” (Woods, 2016) is a term coined by data scientist Fred Beneson who makes the point that just because they use math does not discount any inherent subjectivity. Cathy O’Neil has the same belief; “Big data doesn’t eliminate bias, we’re just camouflaging it with technology” (O’Neil, 2016). Thus, algorithms are only as good as the information used in their design. Human bias built big data, Du Gay and Pryke (2002) state that “accounting tools… do not simply aid the measurement of economic activity, the shape the reality they measure”. The challenge here then is not just that these tests perpetuate prejudicial judgments but firstly that they can do this on a much larger scale than when previously done manually; secondly the disingenuousness that a mathematical test must be objective means they are accepted without resistance in most cases. In the last ten years the introduction of new software (Blackboard, Moodle, and ClassDojo) for individualised learning in schools has produced numerous opportunities for developing the education process while also generating multiple legitimate concerns. The compiling of student profiles and information can later be sold to data brokers, future employers, and universities (Kitchin, 2014). The good news about algorithms and big data in education is that it can be advantageous for personalising teaching, in particular within the e-learning industry and remote learning (Fernández, 2014). On the converse, however, the rise of algorithms and big data bring many ethical issues. Companies like Google have increased the services they offer to include email, document storage, e documents, news, web browsing, social networking and anything else that might interest their users. Such companies gain access to more personal data, which they collect, store, and cross-reference (Boyd and Crawford, 2012). Information that is accessible to the public, is assembled from different sources into a comprehensive profile, thus, creating a revealing portrait of a person. Although everyone in society use these devices and application, students cannot progress through their course without using these technologies, they are obligated to submit assignments via their account, and use ecards in library etc. Student’s information may be used against when applying to continue their education or when applying for jobs. Information may be interpreted negatively, for example, if a student has many library fines that have yet to be paid, or spent more time in the campus bar than in the library, these can give negative perceptions about the person’s character, when in fact they were engaging in study groups in the campus bar, or that their overdue library fine is being disputed or was an irregularity. All of this information about a person can have a ripple affect going into their adult life, all of which was deciphered without human intervention. Before the rise of Big Data, consumers were generally exposed to the same advertising and consumer messages, via a standard set of media- posters, newspapers, television, etc. However, Big Data has changed the rules. Individuals are treated differently based on their metadata, for example their browsing history, online shopping habits, or the types of articles they read in electronic magazines and newspapers. The first issue, is that this creates a problem of awareness, salience, and consent. Research undertaken by Madden and Rainie (2015) found that 50% would like to block online advertisers from saving records of their activity. Is it acceptable that users are unaware that they are being specifically targeted, is this a problem, does this lead to unhealthy consumerist behaviours? is it such a bad thing that you will be targeted to buy something you might want or need? secondly, is the threat that users online privacy is compromised? Although consent is given, as Fred Cate (2013) argues, the reality is nobody reads the convoluted policy documents. More importantly, it could be considered that consent is not informed since they cannot predict the future uses of their personal data, Schonberger (2013) proposes. It is this secondary use of information that has become the issue in relation to privacy laws. Companies such as Google are unlikely to embark on a backdated crusade to obtain permission from users to use their previous search history to gather information: it would be both costly and time-consuming. Despite these issues the majority of citizens continue to use data-collecting services such as Google or Facebook without appropriately protecting their privacy by means of proxy servers, encryption, or any other technical measures. As Maddie and Rainie (2015) identified, only 7% of adults in the U.S.A. were confident that their records would remain private and secure with online advertisers. This creates another issue, the issue of the ‘lock in’ effect, relating to the fact that in order to keep up with society you have to have an online presence. Users remain loyal even though their information has been compromised. and they often don’t have the ability to protect their privacy (Strater and Lipford, 2008). Furthermore, the consequences of Big Data collecting private information can have much more far-reaching consequences than simply bombarding one with personalised advertisements. It can prevent people from obtaining mortgages, bank loans, insurance, and housing (O’Neil, 2016). For example, if someone has been overdrawn continuously finance institutions will see this and perceive them as high risk where the fact could be that they are constantly using account for work expenses which take time to be reimbursed. Furthermore, if someone’s online shopping habits corelate to an unhealthy diet and can be seen as a health risk they may not be successful in getting health insurance or their premiums may be too costly. Schronberger (2013) describes this excellently as a “dictatorship of data”. The scale of mass surveillance by governments around the world through, for example, the collection of metadata and the monitoring of social media shocked everyone in the post- Snowden society. Data mining and surveillance techniques such as images, videos, and interactive maps as well as associated metadata such as geolocation information and time and date stamps are all used within the policing and national security backgrounds. These raise serious human right rights concerns about the ability of modern states to monitor, dominate and control their citizens (Haraszti et al, 2010). As Schonberger (2013) states, this is reminiscent of the days of the Stazi in East Germany- thousands were employed to monitor the public, collecting multiple miles of documentation. In our modern society an equal amount of data is gathered on each individual. This is collected when we use our phones, devices, debit cards, travel cards, and social security cards, all of which are near impossible to avoid using in the modern world (Bernal, 2016). Unlike the Stazi, companies such as Amazon, Google etc. are not law enforcement agencies; but there is evidence to suggest that government security agencies may be gathering our personal information. The National Security Agency (NSA) are alleged by the Washington Post (Priest and Larkin, 2010) to intercept and store 1.7 billion communications every day. This indicates that changed immensely since the days of the Stazi; with the rise of technology and big data it has become far easier to compile information on the public. This information is gathered not to investigate in the present but rather to have a head start when or if someone becomes of interest to law enforcement or government agencies, O’Neil (2016) gives the example of PredPol, a predictive policing tool. As put by Schonberger (2013), the danger of big data will shift from ‘privacy to probability.’ For example, predicting crime in advance of it happening, using algorithms to predict which areas for police to patrol. This is reminiscent of O’Neil’s (2016) idea of the “pernicious feedback loop” where the already discriminated become more targeted. There are other results that can occur from this too. Does digital surveillance mean we are heading towards a world of constant surveillance and the auto-policing of Orwell’s 1984? Due to the constant surveillance, the public may change their behaviours. This phenomenon has been described by Tijmen Schep (2018) with the following quote-“like oils leads to global warming, data leads to social cooling”. “social cooling” He states this is a concept relating to the negative effects of living within a “reputation economy”. This brings up similarities with Focualt’s panopticism (1979) and can be defined as, “a type of power that is applied to individuals in the form of continuous individual supervision”. The result of “social cooling’ is making society better behaved (at least where they can be observed) but the argument is that it is making people less human. Society’s data is compiled and categorised into scores and compared against the information of others to form a pattern and guess the details of a person. Here are some of the categories used, religious views, agreeableness, sexual orientation, and even ‘had abortion’ or rape victim to name just a few. It is considered that these factors may restrict people in taking risks or expressing their views on political or social issues and hence cool down society. One of the major difficulties of big data and algorithms is the obvious inequalities they foster; inequalities that may have already existed but have been made easier and occur on a much wider scale when employed via technological advances. It appears that those who are disadvantaged in society- prisoners, low-income workers- are particularly vulnerable to the formulas which seek to effect cost savings for large institutions. While such biases may always have existed, technology has facilitated a situation whereby they are considered more acceptable under the mistaken premise that science is non-discriminatory. In some cases, the fact that such algorithms are being used for particular outcomes is unclear, bringing up issues around the ethics of such methods. One of the bigger challenges of Big Data is how to manage digital footprint – everywhere the public go they leave behind a distinct picture of their personality and characteristics. It is considered that societal shifts may occur where people will seek to manage their privacy by changing their publicly recordable behaviours- a mammoth task considering all the different aspects of our lives which can now be monitored. There are few legal protections in place- do governments need to legislate for this or are they complicit in the data-gathering to monitor their citizens? It would seem that the technological progress which has occurred evolved faster than society’s ability to adapt accordingly and there is significant danger that the “information superhighway” will lead us on a journey to a world where privacy is a public commodity. References – Bernal, P., 2016. Data gathering, surveillance and human rights: recasting the debate. Journal of Cyber Policy, 1(2), pp.243-264. Boyd, D. and Crawford, K., 2012. Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, communication
EC 200 Rasmussen College Mod 02 Observation and Assessment Paper
online homework help EC 200 Rasmussen College Mod 02 Observation and Assessment Paper.
EC200/EEC2613 Section 01 Observation and Assessment in Early Childhood Education Module 02 Written Assignment – Letter to Families about Observation and AssessmentNow that the educators in the program have been trained in observation and assessment practices, the families will need to be informed as well.In this assignment, you will be writing a letter/email communication to families describing observation and assessment and how the program will ensure ethical practices.InstructionsWrite a letter/email communication that contains:A welcome (1 paragraph) thatIncludes an appropriate opening salutation.Introduces the topic of observation and assessment being used in your program.Why it is being used and how the family will be included.Overview of observation and assessment practice in the program (1-2 paragraphs):Why observation/assessment is needed (more in-depth than introduction)Who will be observing/assessing?What will be observed/assessed?How their child/children will be observed/assessed?Where will these observations/assessments take place?When can they expect observations/assessment results?Description of how observation and assessment practices in their program will be ethically sound (2 paragraphs) that explains:How observation/assessment practices will be aligned to the NAEYC Code.How observation and assessment practices are directly aligned to the PILES Domains Milestones and State Early Learning Standards.Conclusion (1 paragraph) thatSummarizes the information in about 3-5 sentences.Ends with appropriate closing salutation and your name.Meets the following general requirements:Follows proper conventions of spelling, grammar and writing.Attach one article from a credible source to help families understand observation and assessment.Provides APA in-text citations from credible sources in letter.Provide references for article and at least 1 additional credible source in APA format.
EC 200 Rasmussen College Mod 02 Observation and Assessment Paper
King Abdulaziz University Witnessing George Floyd Stepping Into Shoes Paper
King Abdulaziz University Witnessing George Floyd Stepping Into Shoes Paper.
I’m working on a criminal justice question and need support to help me understand better.
about George Floyd incident
Assignment: “Step in My Shoes”
Introduction – describe the shoes that I will be stepping in and why;
Body – Paragraph 1: Step in the shoes of an observer of the George Floyd incident and describe the stress you are feeling during this incident.
Paragraph 2: Step in the shoes of George Floyd and describe the stress you may be feeling during this incident.
Paragraph 3: Choose 2 people (example – Juror, Judge, Witness (provide the name with the exception of the juror) and discuss and describe the type of stress you have incurred during the trial and why you are feeling this type of stress.
Conclusion on stress of stepping in someone else’s shoes.
King Abdulaziz University Witnessing George Floyd Stepping Into Shoes Paper
A Review Of The Novel Alias Grace English Literature Essay
Grace Marks is one of the two accused for the murders of her employer, Mr. Kinnear and his housewife, Nancy. She was sentenced to life imprisonment. Initially she claims that she does not remember what happened at the scene of the crime. Grace is introverted and carefully chooses what she says so that she does not reveal much information about herself. After Dr. Jordan comes, she opens up a little and tells him her tough childhood and what she remembers about the murders. By the end of the novel, Grace is pardoned, marries her lover, Jamie Dr. Simon Jordan is the physician that is to analyze Grace. He is interested in her circumstances and wants to use what he knows about psychology to pry as much information from her as possible so that it can be determined whether or not she really is suffering from amnesia. After entering in a relationship with Mrs. Humphrey, his landlady, and the results of Grace’s hypnotism, Dr. Jordan becomes disillusioned. He is unable to come to a conclusion and in the end just returns to Europe. Mary Whitney is a girl about Grace’s age who also worked for Mrs. Parkinson. Mary is more experienced with worldly matters and thus becomes sort of like a mentor to Grace. It is through Mary that Grace is able to find family. They are like sisters and become close to each other. She has an affair with Mr. George that ends up in a pregnancy and a failed abortion that takes away her life. Grace seems to care more for Mary than her own mother because when her mom died, she thought twice about using the sheet to cover her. On the other hand, Grace uses her money to provide the best possible funeral for her friend. Supposedly, the spirit of Mary resides in Grace and will come out during hypnotism. Nancy Montgomery is the housemaid of Mr. Thomas Kinnear. When she is first introduced, she is looking for extra help. She is not as welcoming or friendly as Grace’s last employer, Mrs. Parkinson. She feels as though she is superior to Grace. Nancy has an affair with Kinnear and gets jealous of Kinnear when he starts lusting for Grace. She is later found in the cellar, strangled and her throat cut. 4. Conflicts: One major conflict in the novel is determining Grace’s innocence and also her identity. Much of the book is concerned about Grace giving the readers background information about herself and her version of what happened during the time of the murders The conflict never gets resolved because Dr. Jordan never comes to a conclusion and just abandons his all of his findings. He does not know what to think after he witnesses the spirit of Mary Whitney possess Grace’s body. Atwood gives you all of many small pieces and it is up to readers to put everything together and then decide whether or not Grace is guilty or not 5. Opening chapter or scene: Alias Grace opens with a dream about Nancy, a dream that also occurs again later on in the novel. The year is 1851 and Grace is twenty-four years old. She has been in prison ever since she was sixteen. She tries to be the model prisoner even though life in the penitentiary is described as tough. She tells this dream to Dr. Jordan when they arrive at the part of the story. In the next section is a little poem that gives a quick but somewhat inaccurate summary of what has already happened before the novel started. The opening gives some background information about Grace’s life and also foreshadows many events. 6. Plot: Grace has been kept at the Kingston Penitentiary when Dr. Jordan comes and performs his project with Grace, the inciting incident After Grace’s initial reluctance to participate with Dr. Jordan ends, the rising action occurs when Grace relates her past to him. She is an immigrant from Ireland to Canada and suffers from a dysfunctional and poverty-stricken family. Life was hard for her because her father was worthless. She was able to find a job as a housekeeper. While working, she befriends Mary Whitney. She is traumatized when Mary dies because of an unsuccessful abortion and quits her job. She takes up another job with Nancy Montgomery, who works at the Kinnear estate She also meets James McDermott, another worker under Mr. Kinnear. Nancy and Mr. Kinnear seem to have a relationship together but now Kinnear is paying more attention to Grace. James thinks that Nancy and Kinnear should be killed. Grace then tells Dr. Jordan that James kills them both and then faints when James threatens her. When she awakens, James says that she must keep her part of the deal which implied that she was to go to bed with him. Grace tries to put him off and persuades him to escape to Toronto but they soon get captured. In the climax, Dr. Dupont hypnotizes Graces but instead a spirit comes out saying that she is not Grace but Mary Whitney. When the trance is broken, Grace comes back but does not remember what happened during the hypnosis. 7. Conclusion: In the novel’s falling action and conclusion, a disoriented and confused Dr. Jordan ceases his investigations and returns back to Europe Grace is pardoned and released from the penitentiary at the age of forty-five. She ends up marrying her childhood lover, Jaime Walsh and soon gets pregnant. The novel ends with a passage about how Grace will quilt the Tree of Paradise. She will interweave Mary’s petticoat, her prison nightdress, and Nancy’s dress altogether. The ending was only somewhat appropriate because it did not really feel as if he flowed with the rest of the story, that it did not belong there. It just seems attached on. 8. Themes: One theme of the novel is gender and feminism in the nineteenth century. Women back then were supposed to act a certain way. They were to be submissive and modest with the men dominating. Women were also thought to be more petite and moral. This may be a reason why James was executed and why Grace was only sent to prison. Another theme of the novel is that of sexuality. This theme seems to be a big driving force in the story. Mary Whitney gets involved in a sexual affair that has big repercussions. While in prison Grace must deal with the verbal abuse and sexual advances of the guards. Grace is accused of having a sexual encounter with Jamie in the orchard. Also when Mrs. Humphrey’s husband leaves her, she turns to a sexual relationship with Dr. Jordan for comfort. Dr. Jordan, on the other hand has fantasies of Miss Lydia and even Grace. Both Mr. Kinnear and James lust after Grace. Kinnear and Nancy have an affair too. Either way, sexuality plays an important role in the novel. 9. Symbols/Archetypes: One big symbol is that of the quilt. There is both a physical quilt, the one that Grace is working on, and a mental quilt. Each time Dr. Jordan examines Grace, it seems if as though another piece of Grace’s life and identity are sewed onto a quilt. All of the little intricate bits and memories are stitched together make up the whole quilt and there are also different ways to look at and interpret quilts. In addition, the title of each chapter is a name of a real quilting design. Another symbol may be that apples. They could symbolize the truth and knowledge. It could also represent the apple in the Garden of Eden. Grace could symbolize Eve, who was manipulated by something evil and then was punished for it. 10. Parallel events/parallel works: Alias Grace is similar to the story of the Yellow Wallpaper by Charlotte Gillman. Both works of literature were about psychiatric care. Women were the protagonist in both stories. Also both women were isolated from other people, one in an asylum, another in a lonely room. The dream that Grace describes in the opening chapter makes another appearance in the middle of the novel. In it, Grace sees Nancy with blood all over her face. Alias Grace is the retelling of the real story of Grace Marks. It is a historical fiction novel though, so some aspects such as the character of Dr. Simon Jordan are made up. 11. Style: Atwood rarely uses quotations in this novel. This makes the text more confusing as to who is talking and thinking which thoughts. This does emphasize the ambiguity of Grace’s life and her account of the murders In addition to the lack of punctuation, Grace also uses the word “could” very often. This makes it seems like she is making up some of the details, that what she says is conditional The story is presented from the point of view of Grace’s At the beginning of each chapter, Atwood uses a real historical article and/or a quote that describes something about Grace to introduce the next section. To highlight the quilt theme, Atwood also names each chapter after a genuine quilting pattern and even provides a small picture of the design. 12. Significant lines: “I would rather be a murderess than a murderer, if those are the only choices” (23) – showing feminist attitudes “…like passing through the gates of Hell and into Paradise” (447) – when she left the penitentiary and went off into the real world and that is the same with all quilts, you can see them two different ways, by looking at the dark pieces, or else the light” (162) – there are always more than one way to look at things in life and everything has a dark and light side “Murderess is a strong word to have attached to you… (27) – she has a label attached to her and it makes her think a certain way “And so we will all be together” (460) – the last line of the novel, Grace will all of the remnants of her past onto one quilt so that she can look at it and move on