Four Principles to Make Data Tools Work Better for Kids and Families

Posted November 4, 2020
By the Annie E. Casey Foundation
Four principles for using data tools to help kids and families

Advanced data ana­lyt­ics are deeply embed­ded in the oper­a­tions of pub­lic and pri­vate insti­tu­tions and shape the oppor­tu­ni­ties avail­able to youth and fam­i­lies. Whether these tools ben­e­fit or harm com­mu­ni­ties depends on their design, use and over­sight, accord­ing to a report from the Annie E. Casey Foundation.

Four Prin­ci­ples to Make Advanced Data Ana­lyt­ics Work for Chil­dren and Fam­i­lies exam­ines the grow­ing field of advanced data ana­lyt­ics and offers guid­ance to steer the use of big data in social pro­grams and policy.

The report rec­og­nizes that algo­rithms guide deci­sions on every­thing from which neigh­bor­hoods police patrol to which job appli­cants a hir­ing man­ag­er selects to inter­view. It also posits that agen­cies and child advo­cates can use advanced ana­lyt­ics tools to mod­el large, mul­ti­vari­ate prob­lems, pin­point what works, and ele­vate solu­tions that have nev­er been pos­si­ble before.

But many promi­nent civ­il rights orga­ni­za­tions wor­ry that these same tools, which rely on automa­tion and algo­rithms, can wors­en inequities across lines of race, age, income and gen­der. As a result, these groups oppose using advanced ana­lyt­ics to guide deci­sions involv­ing youth and families.

The Foun­da­tion report iden­ti­fies four prin­ci­ples — com­plete with exam­ples and rec­om­men­da­tions — to help steer the grow­ing field of data sci­ence in the right direction.

Four Prin­ci­ples for Data Tools

  1. Expand oppor­tu­ni­ty for chil­dren and fam­i­lies. Most estab­lished uses of advanced ana­lyt­ics in edu­ca­tion, social ser­vices and crim­i­nal jus­tice focus on prob­lems fac­ing youth and fam­i­lies. Promis­ing uses of advanced ana­lyt­ics go beyond mit­i­gat­ing harm and help to iden­ti­fy so-called odds beat­ers and new oppor­tu­ni­ties for youth. 
    • Exam­ple: The Chil­dren’s Data Net­work at the Uni­ver­si­ty of South­ern Cal­i­for­nia is help­ing the state’s depart­ments of edu­ca­tion and social ser­vices explore why some stu­dents suc­ceed despite neg­a­tive expe­ri­ences and what pro­tec­tive fac­tors mer­it more investment.
    • Rec­om­men­da­tion: Gov­ern­ment and its phil­an­thropic part­ners need to test if nov­el data sci­ence appli­ca­tions can cre­ate new insights and when it’s best to apply them.
  2. Pro­vide trans­paren­cy and evi­dence. Advanced ana­lyt­i­cal tools must earn and main­tain a social license to oper­ate. The pub­lic has a right to know what deci­sions these tools are inform­ing or automat­ing, how they have been inde­pen­dent­ly val­i­dat­ed, and who is account­able for answer­ing and address­ing con­cerns about how they work. 
    • Rec­om­men­da­tions: Local and state task forces can be excel­lent lab­o­ra­to­ries for test­ing how to engage youth and com­mu­ni­ties in dis­cus­sions about advanced ana­lyt­ics appli­ca­tions and the pol­i­cy frame­works need­ed to reg­u­late their use. In addi­tion, pub­lic and pri­vate fun­ders should avoid sup­port­ing pri­vate algo­rithms whose design and per­for­mance are shield­ed by trade secre­cy claims. Instead, they should fund and pro­mote efforts to devel­op, eval­u­ate and adapt trans­par­ent and effec­tive models.
  3. Empow­er com­mu­ni­ties. The field of advanced data ana­lyt­ics often treats chil­dren and fam­i­lies as clients, patients and con­sumers. Put to bet­ter use, these same tools can help elu­ci­date and reform the sys­tems act­ing upon chil­dren and fam­i­lies. For this shift to occur, insti­tu­tions must focus analy­ses and risk assess­ments on struc­tur­al bar­ri­ers to oppor­tu­ni­ty rather than indi­vid­ual profiles. 
    • Rec­om­men­da­tion: In debates about the use of data sci­ence, greater invest­ment is need­ed to ampli­fy the voic­es of youth and their communities.
  4. Pro­mote equi­table out­comes. Use­ful advanced ana­lyt­ics tools should pro­mote more equi­table out­comes for his­tor­i­cal­ly dis­ad­van­taged groups. New invest­ments in advanced ana­lyt­ics are only worth­while if they aim to cor­rect the well-doc­u­ment­ed bias embed­ded in exist­ing models. 
    • Rec­om­men­da­tions: Advanced ana­lyt­i­cal tools should only be intro­duced when they reduce the oppor­tu­ni­ty deficit for dis­ad­van­taged groups — a move that will take orga­niz­ing and advo­ca­cy to estab­lish and new pol­i­cy devel­op­ment to insti­tu­tion­al­ize. Phil­an­thropy and gov­ern­ment also have roles to play in help­ing com­mu­ni­ties test and improve tools and exam­ples that already exist.

Casey Foun­da­tion lead­er­ship and staff devel­oped these four prin­ci­ples after broad con­sul­ta­tion with data sci­en­tists, civ­il rights groups, pub­lic lead­ers and fam­i­ly advocates.

There is a sur­pris­ing amount of agree­ment about the val­ues that should guide how we use these tools,” says Chris Kings­ley, senior asso­ciate for data ini­tia­tives at the Casey Foun­da­tion. And ongo­ing debates will con­tin­ue to shape the field and point to areas that need more atten­tion, invest­ment and innovation.”

Down­load a tool kit on equi­ty and data systems

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